Small-area analysis: targeting high-risk areas for adolescent pregnancy prevention programs.
BACKGROUND
Traditional methods of identifying areas in need of adolescent pregnancy prevention programs may miss small localities with high levels of adolescent childbearing.


METHODS
Birthrates for 15-17-year-olds were computed for all California zip codes, and the zip codes with birthrates in the 75th percentile were identified. Panels of local experts in adolescent pregnancy reviewed these "hot spots" for accuracy and grouped them into potential project areas, based on their demographics, geography and political infrastructure.


RESULTS
In all, 415 zip codes exceeded the 75th-percentile cut-off point of 62.8 births per 1,000, and 210 of them differed significantly from the state average of 44.5 per 1,000 for 15-17-year-olds. While all had high adolescent birthrates, they varied greatly in racial and ethnic mix, poverty and educational attainment, and certain perinatal measures such as inadequate prenatal care and repeat pregnancy.


CONCLUSIONS
The use of zip code-level data holds promise for more effective program planning and intervention.
Gould
J B
JB
School of Public Health, University of California, Berkeley, USA.
Herrchen
B
B
Pham
T
T
Bera
S
S
Brindis
C
C
D000293:Adolescent; D001723:Birth Rate; D002140:California / Q000453:epidemiology; D018672:Community Health Planning / Q000379:methods* / Q000706:statistics & numerical data; D003430:Cross-Sectional Studies; D005260:Female; D006801:Humans; D020380:Needs Assessment / Q000706:statistics & numerical data*; D011203:Poverty / Q000706:statistics & numerical data; D011247:Pregnancy; D011253:Pregnancy in Adolescence / Q000517:prevention & control / Q000706:statistics & numerical data*; D011295:Prenatal Care / Q000706:statistics & numerical data; D012111:Residence Characteristics / Q000706:statistics & numerical data; D017062:Small-Area Analysis; D012959:Socioeconomic Factors; D013029:Space-Time Clustering