Psychotropic Medication Prescribing for Children and Adolescents After the Onset of the COVID-19 Pandemic.

Importance: Numerous studies have provided evidence for the negative associations of the COVID-19 pandemic with mental health, but data on the use of psychotropic medication in children and adolescents after the onset of the COVID-19 pandemic are lacking. Objective: To assess the rates and trends of psychotropic medication prescribing before and over the 2 years after the onset of the COVID-19 pandemic in children and adolescents in France. Design, Setting, and Participants: This cross-sectional study used nationwide interrupted time-series analysis of outpatient drug dispensing data from the IQVIA X-ponent database. All 8 839 143 psychotropic medication prescriptions dispensed to children (6 to 11 years of age) and adolescents (12 to 17 years of age) between January 2016 and May 2022 in France were retrieved and analyzed. Exposure: Onset of COVID-19 pandemic. Main outcomes and Measures: Monthly rates of psychotropic medication prescriptions per 1000 children and adolescents were analyzed using a quasi-Poisson regression before and after the pandemic onset (March 2020), and percentage changes in rates and trends were assessed. After the pandemic onset, rate ratios (RRs) were calculated between estimated and expected monthly prescription rates. Analyses were stratified by psychotropic medication class (antipsychotic, anxiolytic, hypnotic and sedative, antidepressant, and psychostimulant) and age group (children, adolescents). Results: In total, 8 839 143 psychotropic medication prescriptions were analyzed, 5 884 819 [66.6%] for adolescents and 2 954 324 [33.4%] for children. In January 2016, the estimated rate of monthly psychotropic medication prescriptions was 9.9 per 1000 children and adolescents, with the prepandemic rate increasing by 0.4% per month (95% CI, 0.3%-0.4%). In March 2020, the monthly prescription rate dropped by 11.5% (95% CI, -17.7% to -4.9%). During the 2 years following the pandemic onset, the trend changed significantly, and the prescription rate increased by 1.3% per month (95% CI, 1.2%-1.5%), reaching 16.1 per 1000 children and adolescents in May 2022. Monthly rates of psychotropic medication prescriptions exceeded the expected rates by 11% (RR, 1.11 [95% CI, 1.08-1.14]). Increases in prescribing trends were observed for all psychotropic medication classes after the pandemic onset but were substantial for anxiolytics, hypnotics and sedatives, and antidepressants. Prescription rates rose above those expected for all psychotropic medication classes except psychostimulants (RR, 1.12 [95% CI, 1.09-1.15] in adolescents and 1.06 [95% CI, 1.05-1.07] in children for antipsychotics; RR, 1.30 [95% CI, 1.25-1.35] in adolescents and 1.11 [95% CI, 1.09-1.12] in children for anxiolytics; RR, 2.50 [95% CI, 2.23-2.77] in adolescents and 1.40 [95% CI, 1.30-1.50] in children for hypnotics and sedatives; RR, 1.38 [95% CI, 1.29-1.47] in adolescents and 1.23 [95% CI, 1.20-1.25] in children for antidepressants; and RR, 0.97 [95% CI, 0.95-0.98] in adolescents and 1.02 [95% CI, 1.00-1.04] in children for psychostimulants). Changes were more pronounced among adolescents than children. Conclusions and Relevance: These findings suggest that prescribing of psychotropic medications for children and adolescents in France significantly and persistently increased after the COVID-19 pandemic onset. Future research should identify underlying determinants to improve psychological trajectories in young people.

Association between air pollution levels and drug sales for asthma and allergy in 63 million people in metropolitan France.

INTRODUCTION: Air pollution is known to have an impact on respiratory health. However, the assessment of this relationship is far from complete and is rarely extended to the country level. We used drug sales data, both Over-The-Counter (OTC) and prescription drugs, to assess exhaustively the impact of air pollution on asthma and allergy at the national level in France. METHODS: The WHO Anatomical Therapeutic Chemical (ATC) classification system was used to describe the distribution of sales of drugs of class R03 (Drugs for obstructive airways diseases, overall for asthma) and R06 (Antihistamines for systemic use). We performed a Quasi-Poisson regression model with a generalized additive model (GAM) to estimate the relationship (Relative Risks and 95% Confidence Interval) between drug sales and air pollutants, that is Particulate Matter with a diameter less than 2.5 micrometers (PM2.5) and less than 10 micrometers (PM10) and Nitrogen dioxide (NO2), as assessed using the high-resolution CHIMERE dispersion model. We designed unadjusted and adjusted single-pollutant models as well as two-pollutant models. RESULTS: PM2.5, PM10, and NO2 were significantly and positively associated with sales of R03 and R06 class drugs, after adjustment for potential confounders. Results were confirmed in the two-pollutant model for PM10 and NO2 but not for PM2.5. CONCLUSIONS: Our study confirms the presence of an association between major air pollutants and the sales of drugs against asthma and allergies. Further studies on larger databases and over several years are necessary to confirm and better understand these results.

Discrepancies in national time trends of outpatient antibiotic utilization using different measures: a population-based study in France.

Objectives: To assess time trends of outpatient antibiotic utilization using different measures and explore their discrepancies. Methods: Based on French sales data from the IQVIA SDM database, 2009-16, we assessed time trends in outpatient antibiotic utilization using PrID, DID, PID and SID (defined as the number of prescriptions, DDDs, packages and standard units per 1000 inhabitants per day, respectively). We explored discrepancies between trends in PrID and DID by modelling the number of DDDs per prescription. Results: Outpatient antibiotic utilization (n = 538.2 million projected prescriptions) decreased in terms of PrID, PID and SID (-10%, -8% and -8%, respectively; negative regression slopes; P < 0.01), but remained stable according to DID (+2%; slope 0.009; P = 0.4). The number of DDDs per prescription increased over time (+14%; slope 0.019; P < 0.001). The proportions of amoxicillin and amoxicillin/clavulanate were positively associated with the number of DDDs per prescription (adjusted coefficients 0.10 and 0.15, respectively; both P < 0.05), as well as the proportion of adult and hospital prescriptions (adjusted coefficients 0.07 and 0.05, respectively; both P < 0.05). The discrepancy between DID and PrID disappeared when the DDD of amoxicillin was increased to values higher than the current DDD. Conclusions: Time trends in outpatient antibiotic utilization expressed as PrID, DID, PID and SID provided conflicting results. We caution against using DID alone when monitoring antibiotic utilization. Instead, we recommend monitoring both DID and PrID as they provide different types of relevant information, especially when studying trends at a national level.