The impact of community risks and resources on adolescent risky behavior and health care expenditures.
OBJECTIVE
To examine a nested model that predicts adolescent risky behavior, health care use, and health care expenditures from individual characteristics, such as age and gender, and community characteristics such as social capital and community-level risky behavior rates.


METHODS
Claims and encounter data were used to classify adolescents enrolled in Florida's Healthy Kids Program into two groups: those who engaged in risky behavior (ARB) and those who did not (NRB). Hierarchical linear modeling techniques were used to predict the odds of risky behavior, the odds of health care use, and health care expenditures based on individual and community characteristics.


RESULTS
ARB consumed significantly more health care services than NRB, and their higher use and charges were attributable not only to individual level factors (i.e., age, gender, presence of special health care need, metropolitan residence status), but also to community level factors (i.e., social capital, risky behavior rates, violence, and ethnic/racial composition) as well. In particular, community investment in social capital predicted lower levels of risky behavior as well as lower health care expenditures.


CONCLUSIONS
This information is important in terms of policy efforts at providing health care for this vulnerable group of individuals, as well as in developing prevention and intervention programs that can be delivered through the health care system and via links to community supports.
Youngblade
Lise M
LM
Department of Epidemiology and Health Policy Research, University of Florida, Gainesville, Florida 32608, USA. lmy@ichp.ufl.edu
Curry
Laura A
LA
Novak
Maureen
M
Vogel
Bruce
B
Shenkman
Elizabeth A
EA
D000293:Adolescent; D000294:Adolescent Behavior; D016497:Adolescent Health Services / Q000191:economics / Q000706:statistics & numerical data*; D000367:Age Factors; D005260:Female; D005544:Forecasting; D005102:Health Expenditures / Q000706:statistics & numerical data*; D006801:Humans; D016014:Linear Models; D008297:Male; D012309:Risk-Taking; D012737:Sex Factors