| Literature DB >> 23227929 |
Stephen R Hughes1, Paul Kay, Lee E Brown.
Abstract
Pharmaceuticals have emerged as a major group of environmental contaminants over the past decade but relatively little is known about their occurrence in freshwaters compared to other pollutants. We present a global-scale analysis of the presence of 203 pharmaceuticals across 41 countries and show that contamination is extensive due to widespread consumption and subsequent disposal to rivers. There are clear regional biases in current understanding with little work outside North America, Europe, and China, and no work within Africa. Within individual countries, research is biased around a small number of populated provinces/states and the majority of research effort has focused upon just 14 compounds. Most research has adopted sampling techniques that are unlikely to provide reliable and representative data. This analysis highlights locations where concentrations of antibiotics, cardiovascular drugs, painkillers, contrast media, and antiepileptic drugs have been recorded well above thresholds known to cause toxic effects in aquatic biota. Studies of pharmaceutical occurrence and effects need to be seen as a global research priority due to increasing consumption, particularly among societies with aging populations. Researchers in all fields of environmental management need to work together more effectively to identify high risk compounds, improve the reliability and coverage of future monitoring studies, and develop new mitigation measures.Entities:
Mesh:
Substances:
Year: 2012 PMID: 23227929 PMCID: PMC3636779 DOI: 10.1021/es3030148
Source DB: PubMed Journal: Environ Sci Technol ISSN: 0013-936X Impact factor: 9.028
Summary of Journal Sources for the 236 Studies Included in the Full Database
| journal | record count | % total (236) |
|---|---|---|
| 42 | 17.80 | |
| 34 | 14.41 | |
| 34 | 14.41 | |
| 33 | 13.98 | |
| 27 | 11.44 | |
| 23 | 9.75 | |
| 11 | 4.66 | |
| 9 | 3.81 | |
| 9 | 3.81 | |
| 8 | 3.39 | |
| 1 | 0.42 | |
| 1 | 0.42 | |
| 1 | 0.42 | |
| 1 | 0.42 | |
| 1 | 0.42 | |
| 1 | 0.42 |
Figure 1Number of publications per year for the 236 published studies included in the database shows a rapid increase after 2003.
Summary of Occurrence Data for the Top 61 Most Frequently Studied (1st to 50th) Pharmaceutical Compounds in Freshwater Ecosystems
| compound | compound type | median concn (ng L–1) | max concn (ng L–1) | no. observations | mean detection frequency | references |
|---|---|---|---|---|---|---|
| amoxicillin | antibiotics | 59.9 | 622.0 | 5 | 29.8 | ( |
| amphetamine | illicit drugs | 10.3 | 50.0 | 5 | 29.7 | ( |
| aspirin (acetylsalicyclic acid) | painkillers | 662.6 | 90 000.0 | 22 | 81.3 | ( |
| atenolol | other cardiovascular drugs | 90.9 | 859.0 | 24 | 83.0 | ( |
| atorvastatin | blood lipid regulators | 39.7 | 101.0 | 5 | 18.2 | ( |
| azithromycin | antibiotics | 188.4 | 1546.7 | 6 | 40.8 | ( |
| benzoylecgonine | painkillers | 72.8 | 770.0 | 10 | 74.6 | ( |
| bezafibrate | blood lipid regulators | 85.0 | 15 060.0 | 38 | 58.0 | ( |
| carbamazepine | antiepileptics | 174.2 | 11 561.0 | 98 | 85.0 | ( |
| chlortetracycline | antibiotics | 142.0 | 2800.0 | 8 | 18.2 | ( |
| cimetidine | gastro-intestinal drugs | 97.3 | 1338.0 | 9 | 47.5 | ( |
| ciprofloxacin | antibiotics | 163 673.5 | 6 500 000.0 | 17 | 33.4 | ( |
| citalopram | antidepressants | 19.8 | 219.0 | 6 | 100.0 | ( |
| clarithromycin | antibiotics | 16.5 | 260.0 | 13 | 53.9 | ( |
| clindamycin | antibiotics | 20.6 | 1100.0 | 8 | 48.0 | ( |
| clofibric acid | blood lipid regulators | 136.2 | 7910.0 | 26 | 52.9 | ( |
| cocaine | illicit drugs | 9.3 | 115.0 | 9 | 49.8 | ( |
| codeine | painkillers | 49.6 | 1000.0 | 17 | 64.4 | ( |
| diazepam | other CNS drugs | 8.7 | 33.6 | 9 | 59.6 | ( |
| diclofenac | painkillers | 136.5 | 18 740.0 | 80 | 75.5 | ( |
| diltiazem | other cardiovascular drugs | 13.0 | 146.0 | 13 | 36.3 | ( |
| diphenhydramine | respiratory drugs | 88.7 | 1410.6 | 6 | 28.7 | ( |
| doxycycline | antibiotics | 25.9 | 400.0 | 5 | 23.7 | ( |
| enalpril | other cardiovascular drugs | 316.7 | 1500.0 | 6 | 25.6 | ( |
| enrofloxacin | antibiotics | 5754.0 | 30 000.0 | 5 | 38.0 | ( |
| erythromycin | antibiotics | 50.8 | 90 000.0 | 32 | 55.5 | ( |
| fluoxetine | antidepressants | 17.8 | 596.0 | 12 | 29.2 | ( |
| furosemide | other cardiovascular drugs | 28.3 | 630.0 | 7 | 58.7 | ( |
| gabapentin | antiepileptics | 208.1 | 1887.0 | 5 | 94.2 | ( |
| gemfibrozil | blood lipid regulators | 103.3 | 7780.0 | 52 | 45.3 | ( |
| ibuprofen | painkillers | 503.8 | 31 323.0 | 92 | 63.0 | ( |
| indomethacin | painkillers | 51.0 | 380.0 | 11 | 41.9 | ( |
| ketoprofen | painkillers | 97.0 | 2710.0 | 38 | 40.1 | ( |
| lincomycin | antibiotics | 23.2 | 730.0 | 11 | 50.3 | ( |
| mefenamic acid | painkillers | 26.3 | 366.0 | 14 | 51.3 | ( |
| metoprolol | other cardiovascular drugs | 104.5 | 8041.1 | 22 | 89.6 | ( |
| morphine | painkillers | 6.5 | 108.0 | 8 | 45.9 | ( |
| naproxen | painkillers | 98.0 | 19 600.0 | 65 | 69.0 | ( |
| norfloxacin | antibiotics | 11 412.4 | 520 000.0 | 11 | 52.3 | ( |
| ofloxacin | antibiotics | 628.6 | 11 000.0 | 16 | 60.0 | ( |
| oxytetracycline | antibiotics | 74 757.7 | 712 000.0 | 11 | 50.0 | ( |
| paracetamol | painkillers | 148.2 | 15 700.0 | 35 | 51.6 | ( |
| pentoxifylline | other cardiovascular drugs | 197.1 | 299.1 | 5 | 39.6 | ( |
| primidone | antiepileptics | 70.9 | 590.0 | 5 | 75.8 | ( |
| propranolol | other cardiovascular drugs | 18.8 | 590.0 | 22 | 69.4 | ( |
| propylphenazone | painkillers | 31.4 | 180.0 | 5 | 94.0 | ( |
| ranitidine | gastro-intestinal drugs | 26.5 | 570.0 | 11 | 35.3 | ( |
| roxithromycin | antibiotics | 20.4 | 2260.0 | 11 | 49.0 | ( |
| salbutamol | respiratory drugs | 25.3 | 1440.0 | 8 | 39.9 | ( |
| sotalol | other cardiovascular drugs | 101.6 | 1820.0 | 10 | 96.0 | ( |
| sulfachloropyridazine | antibiotics | 34.3 | 70.0 | 5 | 3.3 | ( |
| sulfadiazine | antibiotics | 62.6 | 2312.0 | 5 | 48.6 | ( |
| sulfadimethoxine | antibiotics | 9.7 | 3955.6 | 15 | 44.2 | ( |
| sulfamethazine | antibiotics | 146.1 | 6192.0 | 12 | 30.1 | ( |
| sulfamethoxazole | antibiotics | 83.0 | 11 920.0 | 77 | 66.9 | ( |
| sulfapyridine | antibiotics | 11.5 | 12 000.0 | 8 | 75.5 | ( |
| sulfathiazole | antibiotics | 6.2 | 960.6 | 8 | 47.7 | ( |
| tetracycline | antibiotics | 41.5 | 300.0 | 10 | 45.0 | ( |
| tramadol | painkillers | 801.6 | 7731.0 | 5 | 87.0 | ( |
| trimethoprim | antibiotics | 53.4 | 4000.0 | 49 | 49.8 | ( |
| tylosin | antibiotics | 12.5 | 280.0 | 7 | 35.4 | ( |
Mean detection frequency is the mean of all stated or calculated detection frequencies (no. positive detections/no. samples analyzed) for that particular compound. Sixty-two studies representing 32.2% of all database records did not state a detection frequency, or sampling numbers to enable its calculation.
Figure 2Global-scale distribution of the number of published studies identifying pharmaceuticals in inland surface waters.
Figure 3Number of published studies detecting at least one pharmaceutical compound in (a) European regions, (b) North American states, and (c) south Asian provinces.
Figure 4Relative frequency of detection and median concentration of pharmaceuticals in receiving waters: (a) global, (b) Europe, (c) North America, and (d) Asia. (The circumference of each fan is scaled by the relative proportion of detections. Each point outward on the radial axis represents 10 of the median concentration in ng L–1. For example, the innermost circle represents 101 ng L–1; the second represents 102 ng L–1, etc.)
Figure 5Comparison of national averages of pharmaceuticals to the global average for (a) the 1st to 5th and (b) the 6th to 10th top countries (as determined by number of entries in the database; represented by the number in brackets. Global mean is the mean concentration for all records of that compound group). (Values exceeding 200% of global mean: Spain (blood lipid regulators 441%, other cardiovascular drugs 213%, painkillers 209%), Germany (antidepressants 246%), South Korea (other cardiovascular drugs 404%)).
Figure 6Boxplots of the 20 most commonly encountered pharmaceuticals in (a) European, (b) North American, and (c) Asian receiving waters. n values represent total number of records for the respective region and values above the x axes represent records for each of the 20 specific compounds. (Boxes represent interquartile ranges with median concentration represented by the horizontal line. Whiskers show the range of data and asterisks represent outliers).
Figure 7Pie chart summarizing sampling methodologies employed in detection of pharmaceutical compound(s) in rivers. (n = number of records in the database; POCIS = polar organic contaminant integrative sampler).
Figure 8Summary of chronic ecotoxicological data for pharmaceuticals and freshwater organisms across (a) antibiotics, (b) antidepressants, (c) blood lipid regulators, (d) other cardiovascular drugs, (e) others, and (f) painkillers; data summarized from refs (17, 20, 21, and 177).