Table 4.

Coefficient Estimates Using Ordinary Least Squares and Quantile Regression^a

Variableb	OLSc	Q10d	Q50d	Q90d
Total population	0.93***	1.01***	0.94***	0.83***
Median family income	−0.23***	−0.17*	−0.30***	−0.16**
Black non-Hispanic residents	0.02**	0.04**	0.03***	0.00
Hispanic residents	0.09***	0.10***	0.10***	0.10***
Number of births to immigrant mothers	−0.09***	−0.10***	−0.11***	−0.09***
Number of births to unwed mothers	0.06***	0.01	0.04*	0.10***
Number of non-ACS admissions	1.34***	1.46***	1.31***	1.29***
New York City indicator	0.16***	0.18***	0.14***	0.16***
Rural indicator	0.16***	0.12**	0.18***	0.16***
Constant	−10.13***	−11.73***	−10.00***	−8.87***
R2e	0.97	0.81	0.83	0.82

^aDependent variable is the natural log of total ambulatory care sensitive (ACS) admisisons at the zip code level (n=811).

^bAll continuous variables measured in natural logs.

^cOrdinary least squares regression.

^dQ10-quantile regression for 10th percentile. Q50 and Q90 defined analogously.

^eR² is the pseudo R² for Q10, Q50, and Q90.

^***Significant at the 1% level.

^**Significant at the 5% level.

^*Significant at the 10% level.