Ajit Avasthi1, Debasish Basu2, B N Subodh3, Pramod K Gupta4, B L Goyal5, B S Sidhu6, P D Gargi7, Arvind Sharma8, Abhishek Ghosh9. 1. Department of Psychiatry, Postgraduate Institute of Medical Education & Research (PGIMER), Chandigarh, India. Electronic address: drajitavasthi@yahoo.co.in. 2. Drug De-addiction & Treatment Centre (DDTC), Department of Psychiatry, Postgraduate Institute of Medical Education & Research (PGIMER), Chandigarh, India. Electronic address: db_sm2002@yahoo.com. 3. Drug De-addiction & Treatment Centre (DDTC), Department of Psychiatry, Postgraduate Institute of Medical Education & Research (PGIMER), Chandigarh, India. Electronic address: drsubodhbn2002@gmail.com. 4. Department of Biostatistics, Postgraduate Institute of Medical Education & Research (PGIMER), Chandigarh, India. Electronic address: guptapkg@gmail.com. 5. Dr. Vidya Sagar Institute of Mental Health, Amritsar, India. Electronic address: drblgoyal@yahoo.com. 6. Department of Psychiatry, Government Medical College, Patiala, India. Electronic address: drbssidhumd@yahoo.com. 7. Department of Psychiatry, Government Medical College, Amritsar, India. Electronic address: gargpdass@gmail.com. 8. Department of Psychiatry, Guru Gobind Singh Medical College (GGSMC), Baba Farid University of Heath Sciences, Faridkot, India. Electronic address: arvindsharma7557@gmail.com. 9. Drug De-addiction & Treatment Centre (DDTC), Department of Psychiatry, Postgraduate Institute of Medical Education & Research (PGIMER), Chandigarh, India. Electronic address: ghoshabhishek12@gmail.com.
Abstract
BACKGROUND: We used two different yet complementary methods to capture the 'hidden population' of illicit substance users in the state of Punjab, India: Rapid Assessment Survey (RAS) and Punjab Drug Use Monitoring Survey (P-DUMS). METHODOLOGY: For the RAS component, following a pilot study, Respondent Driven Sampling was used to recruit 6600 community-dwelling substance dependent persons aged 11-60 years from all the 22 districts of Punjab. Size was estimated using benchmark-multiplier method, and prevalence was calculated by projecting these data to the source population. For the P-DUMS component, data were collected on 7421 inpatients from 75 government de-addiction centres from 19 districts of Punjab. RESULTS: Subjects In both RAS and P-DUMS were primarily opioid dependent (88% in RAS and 83% in P-DUMS). Heroin (inhaled/injected) emerged as the commonest opioid in both RAS (46%) and P-DUMS (52%), though 30.5% of the RAS sample also used the prescription opioid tramadol. Using the benchmark-multiplier method, 0.27 million (2.5% of the source population) were estimated to be opioid dependent, of which nearly 78,000 (0.7% of the source population) were injecting opioid users (IDUs), predominantly heroin (62%) but also buprenorphine (32.5%). High-risk behaviour was reported by nearly 60% of IDUs. Only 14% of the RAS sample had ever visited any de-addiction centre, and only 2.8% individuals had been admitted to a de-addiction centre in the past year. CONCLUSION: There is a substantive problem of opioid dependence in this difficult-to-reach population of Punjab, with low treatment access. Misuse of prescription opioids along with IDU also raises concern.
BACKGROUND: We used two different yet complementary methods to capture the 'hidden population' of illicit substance users in the state of Punjab, India: Rapid Assessment Survey (RAS) and Punjab Drug Use Monitoring Survey (P-DUMS). METHODOLOGY: For the RAS component, following a pilot study, Respondent Driven Sampling was used to recruit 6600 community-dwelling substance dependent persons aged 11-60 years from all the 22 districts of Punjab. Size was estimated using benchmark-multiplier method, and prevalence was calculated by projecting these data to the source population. For the P-DUMS component, data were collected on 7421 inpatients from 75 government de-addiction centres from 19 districts of Punjab. RESULTS: Subjects In both RAS and P-DUMS were primarily opioid dependent (88% in RAS and 83% in P-DUMS). Heroin (inhaled/injected) emerged as the commonest opioid in both RAS (46%) and P-DUMS (52%), though 30.5% of the RAS sample also used the prescription opioid tramadol. Using the benchmark-multiplier method, 0.27 million (2.5% of the source population) were estimated to be opioid dependent, of which nearly 78,000 (0.7% of the source population) were injecting opioid users (IDUs), predominantly heroin (62%) but also buprenorphine (32.5%). High-risk behaviour was reported by nearly 60% of IDUs. Only 14% of the RAS sample had ever visited any de-addiction centre, and only 2.8% individuals had been admitted to a de-addiction centre in the past year. CONCLUSION: There is a substantive problem of opioid dependence in this difficult-to-reach population of Punjab, with low treatment access. Misuse of prescription opioids along with IDU also raises concern.