Sample

Data were collected from January 2005 through December 2009 from 36,928 enrolees in 85 OTPs located in 34 states. Not all programs began study participation in January of 2005; 70 (82%) OTPs participated for 2 or more years; 12 (14%) participated for at least one year but less than two years; and 3 (4%) for less than one year. All programs were federally approved opioid agonist treatment programs and followed federal methadone treatment protocols that require an opioid-dependence diagnosis and an addiction history of at least one year [8]. The research protocol was approved by the Institutional Review Board of the National Development and Research Institutes, Inc., and oral informed consent was obtained from the study participants. The respondents in this study include treatment seeking persons who reported abusing POs or heroin in the past 30 days and were not in methadone treatment in the previous 30 days. Details of OTP participation and subject recruitment protocol can be found in an earlier publication by our group [4] and are only briefly reviewed here.

OTPs were selected based on our knowledge on which OTPs would most likely participate in the study and to represent regions in the U.S. where prescription opioid (PO) abuse was believed to be prevalent, e.g., non-urban areas, especially those in the Appalachian region. Some OTPs were located in major metropolitan areas such as San Francisco and New York City, where PO abuse among OTP enrolees is believed to be relatively less prevalent. A total of 7,814 respondents were not included in analysis due to missing data on age (n = 1037), age less than 16 years (n = 5), age greater than 70 years (n = 24), missing data on type of opioid use in the month before enrolment (n = 1713), or use of neither heroin nor POs in the month before enrolment (n = 5271), resulting in a sample for analysis of 29,114 OTP enrolees.

Measures

Data Analysis

To account for clustering of the 29,114 patients in 85 OTPs, multinomial logit mixed model analysis with a random intercept [11] was used to predict 1) heroin use only; 2) PO abuse only; and 3) both types of use for individual patients. The xtlogit and gllamm procedures of the Stata program [12, 13] were used to fit these mixed models. In all multinomial logit mixed models, the reference category for the dependent variable of type of opioid use was heroin only. Patient-level predictors included Helmert contrasts of the seven age groups (where each contrast compares one age cohort with all younger respondents) and contrasts of interview year (2005-2009) where the initial year of the survey, 2005, was the reference category. Program-level predictors included urbanicity, U.S. region, and the program average of the age Helmert contrasts. Including the program average of individual age group contrasts disentangles the effects of individual patient age and the effects of the average age of patients in an OTP [14]. While the program average of the contrasts are not of direct interest, including them allows the enrolee-level age contrasts to be interpreted unambiguously as pooled within-OTP regression coefficients. This approach of breaking down the age predictor into within-OTP and between-OTP components is used to estimate the effects of individual age within OTPs [15]. Point-biserial correlations between age and type of opioid use were estimated using the within and between analysis (WABA) approach [16]. The WABA approach decomposes associations between age and type of opioid use into within-OTP and between-OTP components. The Mplus modelling software [17] was used to estimate covariances between age and type of opioid use and variances at each level. These covariances were tested for significance using z-tests and converted to correlations for presentation.

Summary of findings

Patterns of opioid use varied considerably across OTPs. On the whole, while there were some significant associations between individual enrolee age and opioid use, effect sizes were small. Younger enrolees within OTPs had increased odds of using either POs only or both POs and heroin relative to heroin only. Effect sizes were larger for OTP average enrolee age, with heroin use more likely in OTPs with a higher average age and PO only or both PO and heroin use more likely in OTPs with a lower average age.

Enrolees interviewed in more recent years of the study period were more likely to use PO and heroin than heroin only and were more likely to use PO only than heroin only. Enrolees in OTPs located in higher urbanicity areas were more likely to use PO and heroin than heroin only and were more likely to use PO only than heroin only. Enrolees in OTPs located in the Midwest and Southeast regions of the U.S. were more likely than enrolees in OTPs located in the Northeast to use PO and heroin than heroin only and were more likely to use PO only than heroin only. Enrolees located in the West region of the U.S. were more likely than enrolees in OTPs located in the Northeast to use PO only than heroin only. Even after taking into account other factors including interview year, urbanicity, and U.S. region, younger OTP average age of enrolees was associated with an increase in the odds of PO use only and an increase in the odds both PO and heroin use.

Discussion of findings

Consistent with previous research describing differences between heroin and PO users and addiction treatment admissions, we found increases in the probability of only heroin use and decreases in the probability of PO use, with or without heroin use, as individual enrolee age increased. These differences may be due in part to cohort effects, with younger users initiating drug use more recently when POs were more widely available.

While individual enrolee age differences consistent with previous research were found, it should be noted that effect sizes were fairly small. Contrasts of older age groups with younger age groups were typically associated with changes in the odds of a particular type of use that were around only 5%. While our main focus was on the association between individual enrolee age and type of use, we also found that variation in type of use across programs was substantial. This may simply reflect geographic differences in patterns of opioid use. The fact that the average age of enrolees in an OTP was related to opioid use more strongly than individual enrolee age suggests that both age and opioid use vary across OTPs and much of the total association between age and opioid use is at the OTP rather than the enrolee level. In other words, within a single OTP, individual enrolee age is only weakly associated with pattern of opioid use. Previous research examining differences among OTP enrolees with different patterns of use has not taken a multilevel approach. The multilevel approach allows individual enrolee characteristics and OTP characteristics to be disentangled, and we believe that is important for understanding the nature of individual differences in detail. If the nesting of enrolees within OTPs is ignored or if multilevel analysis is not formulated to differentiate associations at enrolee and OTP levels, then associations that primarily operate at the OTP level, and are thus organizational and cultural phenomena, may be misinterpreted as manifestations of the addiction process of the individual.

Many enrolees used heroin and POs in the month before enrolling in an OTP. This pattern of use may be an adaptation to changes in availability of heroin or prescription opioids. While previous research has suggested enrolees using POs generally have fewer problems than heroin users such as addiction severity, criminal activity and injection [3, 4, 20], it would be useful to examine enrolees who use a variety of opioids, including heroin, in more detail.

Consistent with a trend for an increase in first time treatment admissions for heroin among older adults [6], we found that heroin use was more prevalent among older OTP enrolees. We also found that prevalence of PO abuse among younger OTP enrolees is increasing over time, which is consistent with the dramatic increase in all PO treatment admissions for younger persons [5]. The increasing trends in PO abuse in the U.S. suggest that the OTP admissions for this disorder (especially among younger persons) will increase for the foreseeable future.

Since we also found that much of the total association between age and opioid use is at the OTP level rather than the enrolee level, we are likely to see that PO abuse will continue to remain more prevalent in some OTPs than in others. Collectively, a policy implication of these data is that OTPs will need to address the increasing prevalence of PO abuse among their newly enrolled patients and that some OTPs will continue to have a greater proportion of young PO abusing patients than others. Program service needs for young PO abusers compared with older heroin abusers are likely to differ, e.g., more vocational training for the younger and more chronic disease management for the older cohort. A one size fits all model would not be cost efficient. Given the increasing diversity among patients enrolling in opioid treatment (younger PO abusers; older heroin abusers) both within and especially across programs, OTPs will need to have some flexibility in how they utilize program resources. Moreover, policy makers and funders will need to be sensitive to these differences so that resources can be efficiently allocated.

Limitations

Because OTPs were selected to represent U.S. regions where PO use was expected to be prevalent, the sample is not representative of the population of OTP enrolees. However, we do not believe this is a severe limitation. OTPs were sampled across diverse areas around the U.S., across 34 states and various geographical locations. More than half of the study OTPs were located in densely populated urban areas (where PO abuse is generally less prevalent).