key: cord-0755552-mk6x0ija authors: Guzel, Evsen Yavuz; Atasoy, Aslı; Gören, İsmail Ethem; Daglioglu, Nebile title: Impact of COVID- 19 pandemic on antidepressants consumptions by wastewater analysis in Turkey date: 2022-05-12 journal: Sci Total Environ DOI: 10.1016/j.scitotenv.2022.155916 sha: 6302e3a11183622b2b6e8f1b04bc7ae3ff60f716 doc_id: 755552 cord_uid: mk6x0ija The COVID-19 pandemic has been a major challenge worldwide, forcing countries to take restrictive measures beyond conventional methods in their fight against the spread of the disease. Followingly, many studies have been conducted on the effects of these measures on mental health. Wastewater-based epidemiology (WBE) was used in this study to monitor and estimate changes in antidepressant use under normal conditions (2019) and COVID-19 pandemic conditions (2020). Likewise, this study utilized wastewater-based epidemiology (WBE) to monitor and assess changing trends from the pre-pandemic period (2019) to COVID-19 pandemic conditions in antidepressant use (2020). Wastewater samples were collected from 11 cities in Turkey throughout six sampling periods covering the pre-pandemic and during-pandemic periods (June 2019–December 2020). Then, samples were analyzed via LC-MS/MS method. As a result, we observed that venlafaxine was the drug with the highest concentration (mean ± SD: 103.6 ± 112.1 mg/1000p/day). Moreover, city number 6 presented the highest venlafaxine use and the most dramatic increase during the pandemic period. Finally, this study revealed the potential of WBE to estimate the changing trends in mental health during the ongoing pandemic. drugs were analyzed with the LC-MS/MS method in wastewater samples collected from 18 wastewater treatment plants in 11 cities of Turkey during the sampling period. The study consisted of the analysis of antidepressant consumption markers. The targeted compounds were summarized in Table 1 . One of the factors affecting the reliability of the back-calculation is the accuracy of the Correction Factors (CF). Zuccato et al. suggested using a specific CF calculated from the percentages of excretion of six different drugs or their metabolites (cocaine, heroin, amphetamine, methamphetamine, ecstasy, and cannabis) (Zuccato et al., 2008) . Therefore, the following equation was proposed and applied to obtain the CF (Equation 1): )/ ( ) % (eq. 1) Reference standards of the targeted compounds and the corresponding isotopically labeled internal standards were obtained from Sigma Aldrich, Cerilliant (Round Rock, TX, USA). Water and methanol of HPLC grade were purchased from Merck (Darmstadt, Germany). Stock solutions of standards were prepared in methanol and stored at -20 0 C. Calibrators and internal standards were prepared daily. Wastewater samples were collected from 18 wastewater treatment plants located in 11 different cities in Turkey (Table S1 ). 24-hour composite wastewater samples from WWTPs were collected every three months for seven consecutive days, in 6 periods in total, from June As stated earlier, the study concerns changes in trends in the use of antidepressants during the pre-pandemic and the COVID-19 pandemic period. Therefore, to compare the two periods, we defined the interval from June 2019 to December 2019 as "normal conditions", and the interval from June 2020 to December 2020 as "COVID-19 pandemic conditions". The method used in our previous studies was used as the extraction method (Daglioglu et al., 2021) . Initially, water samples were prefiltered through a 0.7 µm glass fiber filter J o u r n a l P r e -p r o o f (Merck Millipore, Cork, IRL) followed by solid extraction (SPE). SPE cartridges (Oasis HLB, and 3 mL of ultrapure water. Water samples (50 mL) were passed through SPE cartridges, rinsed with 3 mL ultrapure water, and dried for 10 minutes. Then, the SPE cartridges were eluted with methanol (twice with 3 mL). Extracts were evaporated to dryness under N2 (Teknosem, TAB-40 WEL, Istanbul, Turkey), and the residue was reconstituted in 500 µL of methanol and transferred to amber glass bottles. Samples were analyzed using a Shimadzu 8040 liquid chromatography-tandem mass spectrometry (LC-MS/MS) (Kyoto, Japan). The chromatographic separation of analytes was performed using a pentafluorophenyl propyl (PFPP) column (Allure 50×2.1 mm i.d., 5 μm, Restek, Bellefonte, PA, USA), maintained at 40ºC. Gradient elution was performed at a flow rate of 0.4 mL/min, using 10 mM ammonium formate in water (A) and methanol ( Table S2 . 2.6. Quality assurance/quality control To determine the extraction efficiency, accuracy, precision, and matrix effect studies, quality-control water samples were conducted at different concentration levels for each analyte by spiking into blank water samples. Analyses at each concentration level were repeated six times. Obtained results of non-spiked water samples were substracted before recovery (Rec) calculations. The standard deviation (SD), relative standard deviation (RSD), and Rec repeatability values were calculated. Rec values for the all analytes was among average 85%-%115 range with a precision (%RSD) below 15%. All extractions were performed along with daily prepared ILIS-added blank water samples, and methanol was injected before each sequence as a check for carry-over. In addition, after every 20 samples, internal quality control samples (spiked with 5, 20, 250, and 450 ng/L for antidepressant drugs) were analyzed. No marked carry-over was observed for all of the analytes. Daily mass loads of biomarkers were calculated by multiplying their concentrations in the 24-h composite samples by the corresponding daily flows of wastewater. Mass loads were then normalized to the number of people served by the WWTP to yield the consumptions (mg/1000p/day). Consumed quantities and per capita intakes were estimated for antidepressants using the following equation 2: Conc. is the concentration of each target analyte (ng/L) in influent wastewater, F is the daily wastewater flow rate (m 3 /day), CF is the specific correction factor for each analyte (Table 1) , and P is the population served by the WWTP. The defined daily dose (DDD) per 1000 people for all antidepressants was calculated according to World Health Organization Collaborating Centre for Drug Statistics Methodology (World Health Organization, 2018). The calculated DDDs for the antidepressants were shown in Table S3 . All statistics were performed by IBM SPSS software v24. Descriptive statistics (mean and standard deviation) were used to characterize population normalized loads of the measured drugs. Mann-Whitney U, one-way ANOVA, and Kruskal-Wallis tests were computed to compare the measurements of the groups. Linear regression analysis was performed to determine the relationship between the estimated SUM of antidepressant consumptions and the number of daily cases in Turkey during the COVID-19 pandemic. Multiple group variability was evaluated statistically by two-way ANOVA. Statistical significance was set at p<0.05. This study presents baseline monitoring data to evaluate the impact of the COVID-19 pandemic on antidepressant drug use in 11 cities in Turkey. As a result, considering the analysis of studied antidepressants, the drug with the highest consumption was venlafaxine J o u r n a l P r e -p r o o f (mean±SD: 103.6±112.1 mg/1000p/day), followed by amitriptyline, clomipramine, citalopram, moclobemide, and mirtazapine, respectively ( Figure 1 ). Meanwhile, opipramol and imipramine were found in lower concentrations than other drugs. Moreover, similar to mg/1000p/day values, the highest consumption amount was observed in venlafaxine according to DDDs calculations in Table S3 , followed by citalopram, amitriptyline, mirtazapine, clomipramine, and moclobemide, respectively. Similarly, the lowest consumption based on DDDs was observed in opipramil and imipramine. Also, the average mass loads observed in both periods varied greatly, as evident in the relative standard deviations (RSD). For instance, the RSD values for venlafaxine and opipramol were 108.2% and 69.3%, respectively. The variation in RSD values was due to concentration differences among cities as well as due to daily, weekly, and temporal changes. The current study's findings show that antidepressant usage increased during the pandemic in Turkey ( Table 2 ). The common practice of monitoring antidepressant use is generally based on population surveys, prescription, and sales data. For instance, it was reported that there was a 68% increase in antidepressant drug sales at the onset of the pandemic (March 2020) in Australia (Tscharke et al., 2021) . However, no such data is available for Turkey. Also, the participants in these surveys are likely to not report drug use for fear of being stigmatized. In addition, due to demanding challenges in processing the data on drug sales in Turkey, it is not possible to keep records of figures. This issue was further realized in the survey study, in which the current prevalence of depressive disorder was estimated in 27 European countries, as it was reported that the data obtained from Turkey were not of satisfactory quality and therefore excluded from the study (Arias- In this study, the mean amount of citalopram was found to be 8.87±9.05 mg/1000 p/day. Since no study has reported the WBE estimated antidepressant use method in terms of DDD unit so far, the consumption figures of other countries were compared in mg/1000p/day. The reported mean amount of citalopram was higher than the amount observed in our study. (Boogaerts et al., 2019) . This study estimated the mean amount of SUM of the antidepressant use as 165.0±157.6 mg/1000p/day. Moreover, examining the cities included in the study noted that the highest usage rate and increase during the covid period were in City 6, followed by City 8, City 1, and City 2 ( Figure 4 ). While the use of antidepressants in City 10 decreased during the covid period, the lowest increases were in City 11, City 9, and City 3, respectively. Also, the total SUM detected in City 6, City 8, City 1, City 5, and City 7, respectively, was higher than the average amount of antidepressant use in Turkey. Finally, in order, the lowest amounts were found in City 11, City 3, City 9, City 2, City 10, and City 4. Venlafaxine and citalopram consumption increased during the pandemic period in all cities except City 10 and City 11 (Table S4) . Moreover, amitriptyline consumption increased during the pandemic period in all regions. In City 11, moclobemide consumption could not be detected in both periods, while opipramol consumption was observed only in the pandemic J o u r n a l P r e -p r o o f period. Finally, clomipramine consumption significantly increased in cities 3 and 6 during the pandemic (p<0.05). This WBE-based approach data showed that long-term antidepressant drug use in the treatment of depression increased during the quarantine period compared to the previous period in Turkey. Additionally, results indicated that the COVID-19 pandemic negatively affected mental health in Turkey in general. Currently , This study showed that antidepressant consumptions increased in 11 cities in Turkey during the COVID-19 pandemic. The highest consumption was detected in venlafaxine, followed by amitriptyline, clomipramine, citalopram, moclobemide, and mirtazapine, respectively. Additionally, results showed that daily antidepressant consumption increased in correlation to the increase in COVID-19 cases. Limited data are available on monitoring the change in antidepressant consumption before and during the COVID-19 pandemic. While more research is needed to understand these changing trends, the findings of this study can help authorities take action in health and public services to prepare for the future challenges of the ongoing pandemic. 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Corresponding authors * laurent Impact of COVID-19 pandemic on mental health in the general population: A systematic review Estimating community drug abuse by wastewater analysis. Environ. Health Perspect All the authors would like to thank the administrators of eighteen WWTPs in eleven countries of Turkey for their help in the sampling of influent wastewaters from WWTPs.