TENDÊNCIA TEMPORAL DE AFASTAMENTO DO TRABALHO POR TRANSTORNO DEPRESSIVO EM SERVIDORES DE UMA UNIVERSIDADE PÚBLICA DO ESTADO DE MATO GROSSO DO SUL (2012 – 2022)

Abstract

The epidemiology of depressive disorder is a growing public health concern. This psychiatric condition affects millions of workers around the world and can cause work disability, mortality, reduced quality of life and low productivity at work. The objective of this study is to know the temporal trend of the evolution of the rates of absence from work due to health problems, specifically depressive disorder, of federal public servants, from the Federal University of Mato Grosso do Sul, in the period between 2012 and 2022. Regarding the method employed, a longitudinal study of time series was developed, two components: Time series analysis and Interrupted time series analysis. The study was conducted with federal civil servants of the executive branch, professors and administrative technicians who had a diagnosis of depressive disorder F32 and F33, according to the 10th version of the International Code of Disease. The information was extracted from the People Management System database of the Federal University of Mato Grosso do Sul. Data collection was carried out by a researcher, in the period of January 2023. Sociodemographic variables were accessed; professionals; number of civil servants away from work due to depressive disorder, based on diagnosis in ICD 10 chapters (F32 and F33); Based on the collected data, annual and monthly leave rates were calculated for the period from March 2012 to March 2022. The descriptive analysis, to characterize the cases of leave, was performed based on the distribution of absolute and relative frequency, including the dispersion measures. For the analysis of trends in leave rates, the Prais-Winsten procedure for generalized linear regression was used, which made it possible to assess whether rates are rising, declining or stationary. The respective confidence intervals (95%) were calculated and the trend whose regression coefficient was not different from zero (p>0.05) was considered stationary. The prediction method used to estimate the interrupted time series analysis was Arima. The results obtained showed that there were 2244 absences from work due to depressive disorder in public servants of the Federal University of Mato Grosso do Sul, from 2012 to 2022, with an average of 36.14 (± 25.035) days, ranging from 1 to 180 days. An increasing trend was observed in the number of days away from Elementary Education (4.718%; p=0.036), for Judicially Separated Marital Status (2.150%; p=0.004) and for the age group up to 51 years (0.601%; p=0.054), which was on the threshold of statistical significance. The interrupted time series analysis showed an increase in the number of departures on line 1 of 0.052 (IC95%: 0.0396 - 0.0637) and a reduction in the number of departures on line 2 of -0.0177 (IC95%: -0.05922 - 0.0238). It is concluded that the trends detected in the grouping variables provided a dynamic diagnosis of the occurrence of absences and their prediction, being useful for managers to plan health interventions aimed at servers. The pandemic crisis produced a reduction effect on the monthly rates of sick leave due to depression.