Journal of Environmental and Public Health Table 1: Opioid treatment program and patient characteristics. % 25 38 17 20 53 29 18 43 33 24 60 9 11 77 3 44 50 34 85 71 73 57 Mean SD Median Minimum Maximum 40 275 15 38 134 347 23 89 10 155 7 13 <1 2 <1 <1 1,186 1,947 200 5,031 4 Program Variables (n = 84) USA Region Northeast Southeast Midwest West Beale urbanicity Metro Area >1 million ≥250 K and <1 million <250 K ZIP code square miles Number of patients sampled Patient variables (n = 23, 141) Miles traveled to OTP ZIP code square miles Age 18–29 30–43 44–81 Male Race/ethnicity African american Hispanic White Other Employed First methadone treatment Pain a reason for treatment Strong urge to use Severe withdrawal Prescription opioid use past 30 days Heroin use past 30 days (57%) may be accounted for by the oversampling of OTPs within regions were prescription opioid use is believed to be prevalent. 3.1. Travel Distance. The average distance traveled from patients’ residence to treatment programs was 15 miles, with a median travel distance of 7 miles and an interquartile range of 3 to 16 miles. More than half of all patients (60%) traveled less than 10 miles, and most patients (94%) traveled less than 50 miles; 26% of the patients traveled more than 15 miles and 2% traveled more than 100 miles to attend their OTP. Figure 1 is a plot of travel distance (untransformed) which shows the central tendency, variability, and shape of the sample distribution in details (The mean and median travel distances were the same for the full sample (n = 23,141) and for the sample included in the linear mixed model analysis (n = 17,792)). 3.2. Mixed-Eﬀects Model for Travel Distance. Prior to control- ling for program and patient level predictors we generated zero-order correlations of these variables with the log transformed value of distance. As can be seen in Table 2, most measures are signiﬁcantly (P < .05) associated with distance. The strongest correlates (r ≥ .20) include urbanicity, ZIP code area of patient’s residence, race/ethnicity, recent prescription opioid use, and no recent use heroin use. In the ﬁrst block of the linear mixed model analysis, urbanicity was related to travel distance. Patients in moder- ately and low populated counties traveled 1.359 and 1.683 times as many miles as patients in densely population urban areas. In the second block, the area of the ZIP code in which the patient resided was related to travel distance. A one-unit increase in the natural logarithm of square miles multiplied the travel distance by 1.360 miles.