| Literature DB >> 32023897 |
Peng Du1,2, Xin Liu3, Guangcai Zhong3, Zilei Zhou2, Margaret William Thomes4, Choon Weng Lee4,5, Chui Wei Bong4,5, Xuan Zhang1, Fanghua Hao1, Xiqing Li2, Gan Zhang3, Phong K Thai6.
Abstract
Southeast Asian countries including Malaysia play a major role in global drug trade and abuse. Use of amphetamine-type stimulants has increased in the past decade in Malaysia. This study aimed to apply wastewater-based epidemiology for the first time in Kuala Lumpur, Malaysia, to estimate the consumption of common illicit drugs in urban population. Influent wastewater samples were collected from two wastewater treatment plants in Kuala Lumpur in the summer of 2017. Concentrations of twenty-four drug biomarkers were analyzed for estimating drug consumption. Fourteen drug residues were detected with concentrations of up to 1640 ng/L. Among the monitored illicit drugs, 3,4-methylenedioxy-methamphetamine (MDMA) or ecstasy had the highest estimated per capita consumptions. Consumption and dose of amphetamine-type stimulants (methamphetamine and MDMA) were both an order of magnitude higher than those of opioids (heroin and codeine, methadone and tramadol). Amphetamine-type stimulants were the most prevalent drugs, replacing opioids in the drug market. The prevalence trend measured by wastewater-based epidemiology data reflected the shift to amphetamine-type stimulants as reported by the Association of Southeast Asian Nations Narcotics Cooperation Center. Most of the undetected drug residues were new psychoactive substances (NPSs), suggesting a low prevalence of NPSs in the drug market.Entities:
Keywords: MDMA; Southeast Asia; ketamine; methamphetamine; substance abuse; wastewater analysis
Mesh:
Substances:
Year: 2020 PMID: 32023897 PMCID: PMC7036889 DOI: 10.3390/ijerph17030889
Source DB: PubMed Journal: Int J Environ Res Public Health ISSN: 1660-4601 Impact factor: 3.390
Statistics of drug residue concentrations (ng/L) in wastewater treatment plant (WWTP)-A and -B.
| Drug Residues | WWTP-A ( | WWTP-B ( | |||||||
|---|---|---|---|---|---|---|---|---|---|
| DF a (%) | Range | Mean ± STD b | Median | DF (%) | Range | Mean ± STD | Median | ||
| Methamphetamine | 100 | 690–1640 | 1014 ± 246 | 956 | 100 | 47–225 | 132 ± 72 | 118 | |
| Amphetamine | 100 | 47–93 | 69 ± 15 | 73 | 100 | <LOQ–22 | 8 ± 7 | 5 | |
| Ketamine | 100 | 188–354 | 274 ± 39 | 284 | 100 | 243–311 | 276 ± 24 | 279 | |
| Norketamine | 100 | 51–106 | 91 ± 14 | 94 | 100 | 146–206 | 175 ± 20 | 174 | |
| Morphine | 100 | 35–93 | 65 ± 14 | 67 | 33 | <LOD–22 | 6 ± 9 | <LOD | |
| Codeine | 100 | 18–45 | 32 ± 8 | 31 | 33 | <LOD–30 | 9 ± 14 | <LOD | |
| 6-acetylmorphine | 20 | <LOD–13 | 2 ± 4 | <LOD | 0 | <LOD | <LOD | <LOD | |
| Cocaine | 100 | 1–11 | 6 ± 3 | 5 | 0 | <LOD | <LOD | <LOD | |
| Benzoylecgonine | 100 | 6–35 | 19 ± 8 | 16 | 0 | <LOD | <LOD | <LOD | |
| MDMA | 100 | 290–1296 | 812 ± 346 | 936 | 100 | 5–52 | 54 ± 59 | 28 | |
| MDA | 95 | <LOD–51 | 28 ± 10 | 29 | 100 | <LOQ–91 | 53 ± 29 | 60 | |
| Methadone | 100 | <LOQ–31 | 10 ± 7 | 10 | 100 | <LOQ–13 | 8 ± 4 | 8 | |
| EDDP | 100 | 3–56 | 31 ± 17 | 37 | 100 | 19–25 | 23 ± 3 | 23 | |
| Tramadol | 100 | 146–265 | 185 ± 30 | 185 | 100 | 490–757 | 639 ± 95 | 634 | |
a DF—detection frequency; b STD—standard deviation.
Mean influent loads (mg/1000 inh/d) of drug residues in WWTP-A and -B.
| Drug Residues | WWTP-A | WWTP-B | ||
|---|---|---|---|---|
| June | July | August | July | |
| Methamphetamine | 207 ± 38 | 201 ± 27 | 295 ± 48 | 30 ± 16 |
| Amphetamine | 15 ± 3 | 14 ± 3 | 19 ± 2 | 2 ± 2 |
| Ketamine | 57 ± 10 | 62 ± 6 | 69 ± 6 | 62 ± 5 |
| Norketamine | 19 ± 3 | 21 ± 3 | 23 ± 1 | 39 ± 5 |
| Morphine | 17 ± 4 | 12 ± 3 | 16 ± 2 | 1 ± 2 |
| Codeine | 8 ± 2 | 7 ± 2 | 7 ± 1 | 2 ± 3 |
| 6-acetylmorphine | <1 | <1 | 1 ± 1 | <1 |
| Cocaine | 1 ± 1 | 1 ± 1 | 2 ± 1 | <1 |
| Benzoylecgonine | 4 ± 12 | 3 ± 2 | 5 ± 2 | <1 |
| MDMA | 195 ± 73 | 145 ± 97 | 221 ± 46 | 12 ± 13 |
| MDA | 6 ± 3 | 7 ± 2 | 6 ± 1 | 12 ± 7 |
| Methadone | 2 ± 1 | 2 ± 2 | 2 ± 1 | 2 ± 1 |
| EDDP | 7 ± 3 | 7 ± 4 | 7 ± 5 | 5 ± 1 |
| Tramadol | 44 ± 9 | 40 ± 5 | 44 ± 6 | 144 ± 21 |
Estimated community consumption (mg/1000 inh/d) and mean dose (dose/1000 inh/d) of drugs serviced by WWTP-A.
| Drugs | June | July | August |
|---|---|---|---|
| MDMA | 748 ± 282 a (7.5) b | 558 ± 373 (5.6) | 850 ± 177 (8.5) |
| Methamphetamine | 481 ± 88 (16.0) | 468 ± 64 (15.6) | 687 ± 112 (22.9) |
| Ketamine | 357 ± 64 (4.8) | 387 ± 35 (5.2) | 434 ± 40 (5.8) |
| Cocaine | 14 ± 6 (0.1) | 9 ± 4 (0.1) | 12 ± 4 (0.1) |
| Tramadol | 150 ± 32 (3.0) | 137 ± 17 (2.7) | 152 ± 21 (5.1) |
| Methadone | 14 ± 7 (0.6) | 15 ± 9 (0.6) | 15 ± 9 (0.6) |
| Codeine | 26 ± 8 (0.7) | 22 ± 6 (0.6) | 24 ± 5 (0.6) |
| Heroin c | 51 ± 11 (3.4) | 38 ± 8 (2.5) | 48 ± 5 (3.2) |
a Consumption (Mean ± STD); b Mean dose; c Assumed the morphine in influents was all coming from heroin abuse.
Figure 1Estimated methamphetamine, MDMA and ketamine consumptions (mg/1000 inh/d) in this study and other countries [3,12,35,36,37,38,39,40,41,42,43,44,45,46].