Efecto del marketing de alimentos poco saludables sobre las preferencias gustativas en escolares

Introduction: The food choice is related to taste preferences and eating habits learned in childhood. Objective: To evaluate the effect of marketing strategies for unhealthy food packaging on the taste preferences of first grade students from elementary schools in the City of Santa Fe, in 2019. Material and method: Intervention study. Through a non-probabilistic convenience sampling, two elementary schools from different socio demographic levels in the city of Santa Fe were selected. Forty-five children of both sexes participated. They were evaluated anthropometrically and participated in the tasting of three pairs of food products, each one presented with its original container and another identical, but white or gray. It was assessed if the taste of each food pair was the same or different. If there was a reported difference, they were asked to indicate the product with the preferred flavor. A self-administered questionnaire inquired about consumption habits and the family environment. Results: 86% of the students evaluated anthropometrically presented excess of weight. Most participants found no difference in taste. Among those who answered that the taste was different, 68% belonged to a more vulnerable social stratum. In addition, more than 90% of boys and girls that perceived a difference in the taste of the product preferred the original packaging. Conclusions: The results of this study, carried out for the first time in Argentina, reinforce the debate on the relevance of a policy that regulates food advertising aimed at children.Introducción: La elección de un alimento tiene relación con preferencias de sabor y los hábitos alimentarios aprendidos en la infancia. Objetivo: Evaluar el efecto de las estrategias de marketing de los envases de alimentos poco saludables sobre las preferencias gustativas de escolares de primer grado de escuelas primarias de la Ciudad de Santa Fe, en 2019. Material y Método: Estudio de intervención. Mediante un muestreo no probabilístico por conveniencia se seleccionaron dos escuelas primarias de diferente nivel sociodemográfico de la ciudad de Santa Fe. Participaron 45 escolares de ambos sexos que fueron evaluados antropométricamente y degustaron tres pares de alimentos, cada uno presentado con su envase original y otro idéntico, pero de color blanco o gris. Se evaluó si el sabor de cada par de alimentos era igual o diferente; y si se registraba la diferencia se solicitaba que señalen el producto del sabor preferido. Mediante un cuestionario autoadministrado se indagó sobre hábitos de consumo y el ambiente familiar. Resultados: El 86% de los escolares evaluados antropométricamente presentaba exceso de peso. La mayoría de los participantes no hallaron diferencias en el sabor. Entre quienes respondieron que el sabor resultó diferente, el 68% pertenece a un estrato social más vulnerable. Además, más del 90% de niños y niñas que percibieron una diferencia de sabor del producto prefirieron el envase original. Conclusiones: Los resultados del presente trabajo, realizado por primera vez en Argentina, refuerzan el debate por la relevancia de un marco normativo que regule la publicidad de alimentos dirigida al público infantil

Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

Background: Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020–21 COVID-19 pandemic period. Methods: 22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution. Findings: Global all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5–65·1] decline), and increased during the COVID-19 pandemic period (2020–21; 5·1% [0·9–9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98–5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50–6·01) in 2019. An estimated 131 million (126–137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7–17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8–24·8), from 49·0 years (46·7–51·3) to 71·7 years (70·9–72·5). Global life expectancy at birth declined by 1·6 years (1·0–2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67–8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4–52·7]) and south Asia (26·3% [9·0–44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations. Interpretation: Global adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic

Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

BACKGROUND: Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020–21 COVID-19 pandemic period. METHODS: 22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution. FINDINGS: Global all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5–65·1] decline), and increased during the COVID-19 pandemic period (2020–21; 5·1% [0·9–9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98–5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50–6·01) in 2019. An estimated 131 million (126–137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7–17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8–24·8), from 49·0 years (46·7–51·3) to 71·7 years (70·9–72·5). Global life expectancy at birth declined by 1·6 years (1·0–2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67–8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4–52·7]) and south Asia (26·3% [9·0–44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations. INTERPRETATION: Global adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic. FUNDING: Bill & Melinda Gates Foundation

Aprendizajes y prácticas educativas en las actuales condiciones de época: COVID-19

“Esta obra colectiva es el resultado de una convocatoria a docentes, investigadores y profesionales del campo pedagógico a visibilizar procesos investigativos y prácticas educativas situadas en el marco de COVI-19. La misma se inscribe en el trabajo llevado a cabo por el equipo de Investigación responsable del Proyecto “Sentidos y significados acerca de aprender en las actuales condiciones de época: un estudio con docentes y estudiantes de la educación secundarias en la ciudad de Córdoba” de la Facultad de Filosofía y Humanidades. Universidad Nacional de Córdoba. El momento excepcional que estamos atravesando, pero que también nos atraviesa, ha modificado la percepción temporal a punto tal que habitamos un tiempo acelerado y angustiante que nos exige la producción de conocimiento provisorio. La presente publicación surge como un espacio para detenernos a documentar lo que nos acontece y, a su vez, como oportunidad para atesorar y resguardar las experiencias educativas que hemos construido, inventado y reinventando en este contexto. En ella encontrarán pluralidad de voces acerca de enseñar y aprender durante la pandemia. Este texto es una pausa para reflexionar sobre el hacer y las prácticas educativas por venir”.Fil: Beltramino, Lucia (comp.). Universidad Nacional de Córdoba. Facultad de Filosofía y Humanidades. Escuela de Archivología; Argentina

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Campus Population Changes in Depression Severity Correlated with the COVID-19 Pandemic

Introduction: Mental health consequences during COVID-19 Pandemic burdened societies. Objective: The aim is to assess the average PHQ-9 in medical visits during pandemic months and compare it with historical data, adapting an existing methodology. Methodology: we used average PHQ-9 score from medical departments, comparing 2020 Fall term data to historical baseline. The increase above baseline and threshold was reported as percentage. We compared the observed average for the current period with the expected average and the higher limit of the 95% confidence interval (CI 95%) derived from historical five years of data. Also, we analyzed the PHQ-9 difference between female and male students for the whole period. Results: Average PHQ-9 for total sample, females and males increased. Difference female- male in scoring was significant. Discussion: In line with national and international literature, our population showed increases in depressive scoring during pandemic months. Women had a higher percentage of increase

Burnout en trabajadores de la salud. Una comparación entre médicos, enfermeras, cargos administrativos y técnicos

Introduction: Healthcare workers (HCW) report higher levels of anxiety, depression, burnout, compared to the general population. The severe global health crisis caused by the coronavirus SARS-CoV-2 brought even more burden to HCW. Objective: To assessed burnout as a whole and in its different domains among HCW in a medical centerMethods: We performed a cross-sectional study examining the association between demographic characteristics, healthcare position and feeling burned out. Data was collected through an anonymous online survey. We utilized the Maslach Survey for Medical Personnel in Spanish. Descriptive analyses summarized age, gender, job role, number of jobs, time in the organization and working in a COVID-19 exposed area. Ji2 tests were used to analyze association between variables and burnout. A multivariate logistic regression analysis was used to identify independent predictors of any of the burnout domains: emotional exhaustion (EE), depersonalization (DP) and/or personal accomplishment (PA). Results: 185/852 subjects answered the survey (21.7%); 79 subjects reported EE (42.7%), 61 (32.9%) DP and 31 (16.7%) PA; 98 (52.4%) had at least one component of high burnout for the dimensions analyzed. Logistics regression shows that female gender (OR= 2.21; 95% CI: 1.12-4.39), administrative positions (OR= 18.61; 95% CI: 4.28-80.93), physicians (OR= 13.27; 95% CI 3.55-49.86), and nurses (OR= 6.55; 95% CI: 1.58-27.14) were strongly associated with the presence of any burnout domain. Conclusions: The overall burnout prevalence was in range with international studies. Female workers, administrative positions, physicians and nurses were identified as independent predictors of burnout.Introducción: Los trabajadores de la salud (TS) informan niveles más altos de ansiedad, depresión y agotamiento, en comparación con la población general. La grave crisis sanitaria mundial provocada por el coronavirus SARS-CoV-2 supuso una carga aún mayor para los trabajadores sanitarios.Objetivo: Evaluar el burnout en su conjunto y en sus diferentes dominios entre los TS en un centro médicoMétodos: Realizamos un estudio transversal donde se examinó la asociación entre las características demográficas, el puesto de atención médica y la sensación de agotamiento. Los datos se recopilaron a través de una encuesta anónima en línea. Utilizamos la Encuesta en español Maslach para Personal Médico. Los análisis resumieron la edad, el género, el rol laboral, la cantidad de trabajos, el tiempo en la organización y el trabajo en un área expuesta a COVID-19. Se utilizaron pruebas de Ji2 para analizar la asociación entre las variables y el burnout. Se utilizó un análisis de regresión logística multivariante para identificar predictores independientes de cualquiera de los dominios del burnout: agotamiento emocional (AE), despersonalización (DP) y/o realización personal (RP).Resultados: Respondieron la encuesta 185/852 sujetos (21,7%); 79 sujetos reportaron AE (42,7%), 61 (32,9%) DP y 31 (16,7%) RP; 98 (52,4%) tenían al menos un componente de burnout alto para las dimensiones analizadas. La regresión logística mostró que el género femenino (OR= 2,21; IC 95%: 1,12-4,39), cargos administrativos (OR= 18,61; IC 95%: 4,28-80,93), médicos (OR= 13,27; IC 95% 3,55-49,86), y enfermeros (OR= 6,55; IC 95%: 1,58-27,14) se asociaron fuertemente con la presencia de algún dominio de burnout.Conclusion: La prevalencia del agotamiento estuvo en el rango de los estudios internacionales. Trabajadoras, cargos administrativos, médicos y enfermeras fueron identificados como predictores independientes de burnout

Burnout analysis in healthcare workers. A one center cross sectional comparison between physicians, nurses, administrative positions and technicians

Introduction: Healthcare workers (HCW) report higher levels of anxiety, depression, burnout, compared to the general population. The severe global health crisis caused by the coronavirus SARS-CoV-2 brought even more burden to HCW. Objective: To assessed burnout as a whole and in its different domains among HCW in a medical center Methods: We performed a cross-sectional study examining the association between demographic characteristics, healthcare position and feeling burned out. Data was collected through an anonymous online survey. We utilized the Maslach Survey for Medical Personnel in Spanish. Descriptive analyses summarized age, gender, job role, number of jobs, time in the organization and working in a COVID-19 exposed area. Ji2 tests were used to analyze association between variables and burnout. A multivariate logistic regression analysis was used to identify independent predictors of any of the burnout domains: emotional exhaustion (EE), depersonalization (DP) and/or personal accomplishment (PA). Results: 185/852 subjects answered the survey (21.7%); 79 subjects reported EE (42.7%), 61 (32.9%) DP and 31 (16.7%) PA; 98 (52.4%) had at least one component of high burnout for the dimensions analyzed. Logistics regression shows that female gender (OR= 2.21; 95% CI: 1.12-4.39), administrative positions (OR= 18.61; 95% CI: 4.28-80.93), physicians (OR= 13.27; 95% CI 3.55-49.86), and nurses (OR= 6.55; 95% CI: 1.58-27.14) were strongly associated with the presence of any burnout domain. Conclusions: The overall burnout prevalence was in range with international studies. Female workers, administrative positions, physicians and nurses were identified as independent predictors of burnout

Psychiatric medication prescriptions increasing for college students above and beyond the COVID-19 pandemic

Abstract Psychiatric medication prescriptions for college students have been rising since 2007, with approximately 17% of college students prescribed medication for a mental health issue. This increase mirrors overall increases in both mental health diagnoses and treatment of university students. As psychiatric medication prescriptions for college students were increasing prior to pandemic, the goal of this study was to compare these prescriptions over the years, while accounting for the added stressor of the COVID-19 pandemic. This study utilized cross-sectional, retrospective data from a cohort of college students receiving care from the university’s health service. We examined prescriptions for mental healthcare from 2015 to 2021. There was a significant increase in the percentage of psychiatric medication prescriptions in 2020 (baseline 15.8%; threshold 3.5%) and 2021 (baseline 41.3%; threshold 26.3%) compared to the historical baseline average for the whole sample and as well as for female students (2020 baseline 21.3% and threshold 4.6%; 2021 baseline 55.1% and threshold 33.7%). Within these years, we found higher trends for prescriptions in April–May as well as September–December. Overall, we found that psychiatric medication prescriptions have continued to rise through the years, with a large increase occurring during the pandemic. In addition, we found that these increases reflect the academic year, which is important for university health centers to consider when they are planning to staff clinics and plan the best way to treat college students with mental health difficulties in the future