Previous Trends Research Articles

PSVI-20 Trends in Mycotoxin Contamination of the 2022 United States Corn Crop

Abstract Mycotoxins are harmful secondary fungal metabolites detrimental to animal health, even at reduced quantities. Focus on clinical signs such as decreased feed intake and vomiting overlook impacts of mycotoxicosis, including increased disease incidence and severity, immune modulation, inflammation, and gastrointestinal disorders. This study was conducted to compare mycotoxin contamination of initial samples of the 2022 corn crop with previous year trends. Samples were analyzed utilizing the liquid chromatography with tandem mass spectrometry (LC-MS/MS) method for six major mycotoxin groups: aflatoxins (Afla), type A trichothecenes (A-Trich), type B trichothecenes (B-Trich), fumonisins (FUM), zearalenone (ZEN), and ochratoxin A (OTA). The 2022 crop year data were compared with the prior four harvest years using GLIMMIX procedure of SAS with harvest year as fixed effect and sample as the experimental unit. A limited number of samples is available thus far (n = 44) as harvest is still progressing, therefore the risk profile of this crop year is likely to change as the sample pool expands. Contamination levels in corn for the tested toxin groups have remained consistent over the survey period. To date, 97% of the samples evaluated contained at least one mycotoxin, compared with 90% that was observed in 2021. The percentage of Afla contaminated samples increased (P < 0.05) in 2022 corn compared with the 2020 and 2021 harvest years (42 vs. 5 and 7%). The percentage of FUM contaminated samples in 2022 corn is greater (P < 0.05) compared with 2020 and 2021 (88 vs. 64 and 64%). The preliminary results of the 2022 US corn crop survey indicate mycotoxin occurrence and contamination levels are similar or greater (Afla and FUM) to the prior crop year and will continue to challenge animal health and performance as these ingredients are fed out.

Disease burden in Norway in 2050: A forecasting analysis based on the Global Burden of Disease (GBD) Study

Abstract Life expectancy in Norway has increased steadily in the past 50 years, in line with decreases in important causes and risk factors for premature mortality. However, due to the aging of the population, it is expected that a higher number will live with chronic diseases in the future. This will have implications for the planning of health services and public health work. The aim of this analysis was to forecast the disease burden in Norway up to 2050. The analyses were based on data on life expectancy and disease burden by 21 disease groups from the Global Burden of Disease Study 2019 (GBD 2019). The population was forecasted to get estimates on future size, age-composition and life expectancy up to 2050. Independent drivers of population health, in terms of sociodemographic factors and a selection of risk factors and preventive measures (e.g. vaccines) were included in the forecasting of general and cause-specific mortality. Non-fatal health loss was forecasted based on incidence/mortality ratios, or previous trends in disease development for causes not associated with mortality. Results are presented as rates, and compared with observed rates from the period 1990 to 2019. Both life expectancy and the proportion of elderly in Norway is forecasted to increase towards 2050. The decreasing trend in mortality and disease burden rates observed from 1990 to 2019 is, however, forecasted to turn, with a forecasted increase starting from 2020 and onward. Mortality due to cancers, neurological diseases and chronic respiratory diseases were forecasted to increase, while cardiovascular diseases were forecasted to contribute with decreased mortality in 2050. The non-fatal disease burden was forecasted to remain relatively stable. Aging of the population is the most important driver of future disease burden. Forecasting of disease burden by cause- and age-groups provides important background knowledge for planning of future health services and targeted health promotion.

Failed secular revolutions: religious belief, competition, and extremism

All advanced economies have undergone secular revolutions in which religious belief and institutions have been subordinated to secular forms of authority. There are, however, numerous examples of failed secular transitions. To understand these failures, we present a religious club model with endogenous entry and cultural transmission of religious beliefs. A spike in the demand for religious belief, due for example to a negative economic shock, induces a new and more extreme organization to enter the religious market and exploit the dissatisfaction of highly religious types with the religious incumbent. The effect is larger where institutional secularization is more advanced, for example where the religious establishment has moderated itself or has been moderated by the political authority. The greater the moderation of the religious incumbent, the more extreme is the position chosen by the religious entrant, and the larger is the rise in religious participation. Hence, unanticipated shifts in religious demand can lead to the emergence of new and more extreme religious organizations and reverse previous trends toward secularization. Our model sheds light on the causes and consequences of failed secular revolutions and religious revivals in Latin America and Egypt.

Sex Differences in Adolescent Depression Trajectory Before and Into the Second Year of COVID-19 Pandemic

Evidence on the impact of the COVID-19 pandemic on adolescent mental health is mixed and does not disentangle natural age-related changes. We compared depressive symptoms among 16-year-olds surveyed, at a fourth wave, before or during the pandemic, while accounting for expected trajectories of within-person change based on 3 prior waves. In this longitudinal cohort of 3,171 adolescents in Tokyo, Japan, adolescents were grouped based on their age 16 survey timing: pre-pandemic (February 2019 to February 2020) and during-pandemic (March 2020 to September 2021). Depressive symptoms were self-reported using the Short Mood and Feelings Questionnaire. Mixed-effect models were fitted to assess group differences while controlling for previous trends. Variations by sex, household income, and pandemic phase (early, late first-year, and second-year) were examined. Of 2,034 eligible adolescents, 960 (455 girls) were assessed before and 1,074 (515 girls) during the pandemic. Overall, depressive symptoms increased by 0.80 points (95% CI 0.28-1.31, 0.15 SD of the population average). This increase varied by sex and pandemic phase. For boys the increase emerged in the late first-year phase and enlarged in the second-year phase (mean difference from pre-pandemic: 1.69, 0.14-3.24), whereas for girls it decreased in the early school-closure phase (mean difference: -1.98, -3.54 to -0.41) and returned to the pre-pandemic level thereafter, with no additional increases during the pandemic. Into the second year of the COVID-19 pandemic, depressive symptoms of 16-year-olds worsened above the expected age-related change only in boys. Continuous monitoring and preventive approaches for adolescents at the population level are warranted. We worked to ensure that the study questionnaires were prepared in an inclusive way. We worked to ensure sex and gender balance in the recruitment of human participants. One or more of the authors of this paper self-identifies as a member of one or more historically underrepresented racial and/or ethnic groups in science. We actively worked to promote sex and gender balance in our author group. The author list of this paper includes contributors from the location and/or community where the research was conducted who participated in the data collection, design, analysis, and/or interpretation of the work.

Trend forecasting and its prospects in Bangladesh RMG industry

To predict the future of RMG business in Bangladesh, trend forecasting analyzes both previous and current fashion trends as well as consumer behavior. Manufacturers and designers can use this data to learn important information about the types of designs, colors and materials that customers will want in the coming months. This information can be used to inform strategic manufacturing and design choices that can increase sales and profitability. The trend forecast outlook in RMG industry in Bangladesh is positive. Attractive clothing is in great demand due to the size and ever-increasing number of fashion-conscious consumers. Additionally, it is the second largest RMG industry worldwide and is still growing rapidly; consequently. To be competitive and meet client expectations, producers and designers must be able to accurately predict trends. Sustainability is an important issue for RMG sector in Bangladesh. To address this, trend forecasting identifies eco-friendly products, processes and designs that may become popular in the near future. Using sustainable techniques minimizes both their social duties and environmental damage. Excellent potential exists in the RMG sector of Bangladesh for trend forecasting. It can help manufacturers and designers stay competitive, meet their consumers' expectations, and move toward more eco-friendly practices by providing analytical insights into purchasing patterns and recent trends.

Analysis of global routine immunisation coverage shows disruption and stagnation during the first two-years of the COVID-19 pandemic with tentative recovery in 2022

Whilst it is now widely recognised that routine immunisation (RI) was disrupted by the COVID-19 pandemic in 2020, and further so in 2021, the extent of continued interruptions in 2022 and/or rebounds to previous trends remains unclear.We modelled country-specific RI trends using validated estimates of national coverage from the World Health Organisation and United Nation Children’s Fund for 182 countries (accounting for > 97% of children globally), to project expected diphtheria, tetanus, and pertussis-containing vaccine first-dose (DTP1), third-dose (DTP3) and measles-containing vaccine first-dose (MCV1) coverage for 2020–2022 based on pre-pandemic trends (from 2000 to 2019).We provide further evidence of peak pandemic immunisation disruption in 2021, followed by tentative recovery in 2022. We report a 3.4% (95 %CI: [2.5%; 4.4%]) decline in global DTP3 coverage in 2021 compared to 2000–2019 trends, from an expected 89.8% to reported 86.4%. This coverage gap reduced to a 2.7% (95 %CI: [1.8%; 3.6%]) decline in 2022, with reported coverage rising to 87.2%. Similar results were seen for DTP1 and MCV1. Whilst partial rebounds are encouraging, global coverage decline translates to a 17-year setback in RI to 2005 levels, and the majority of countries retain coverage at or lower than pre-pandemic levels. The Americas, Africa, and Asia were the most impacted regions; and low- and middle-income countries the most affected income groups.The number of annual Zero Dose (ZD) children – indicating those receiving no immunisations – increased from 12.1 million (M) globally in 2019 to a peak of 16.7 M in 2021, then reduced to 13.1 M in 2022. Overall, we estimate an excess of 8.8 M ZD children cumulatively in 2020–2022 compared to pre-pandemic levels.This work can be used as an objective baseline to inform future interventions to prioritise and target interventions, and facilitate catch-up of growing populations of under- and un-immunised children.

Current Status of Research on Tuina for Analgesia: A Bibliometric and Visual Analysis.

Tuina is a nonpharmacological modality for pain relief that has found applications in the treatment of several pain disorders. Tuina analgesia has been increasingly studied; however, few studies have focused on the previous publication trends, prevalent research areas, collaborations, and other factors. This study aimed to systematically analyze research trends and hot topics in the field of tuina analgesia over the past 30 years, using bibliometric analysis, to inform future research. The web of science database was searched for literature on tuina analgesia from 1992-2023. VOSviewer and CiteSpace were used to analyze annual publication volumes, countries, institutions, journals and CO-cited journals, authorship, articles, and keywords and their relevance, and to perform co-occurrence and clustering analyses. A total of 621 literature elements were included in the analysis. The annual volume of publications has increased steadily in recent years. The top three high-yielding countries were the United States, China, and Canada, respectively. The top three institutional outputs were from Shanghai University of Chinese medicine, Beijing University of Chinese medicine, and McMaster University, respectively. Notably, there was an imbalance between national outputs and centrality, with higher centrality in the United States (0.35) and lower in China (0.01). Cochrane Database of Systematic Reviews was the journal with the most publications (22), and PAIN was the most influential co-cited journals (publications=306). Moreover, current research in this field was dominated by studies on Tuina for relieving postoperative pain, the effectiveness of Tuina analgesia, and Tuina treatment for pain accompanied by anxiety. This study employed bibliometrics to analyze the literature on Tuina for pain treatment over a 30-year period, identifying potential collaborators, institutions, hot topics, and future research trends that will inform potential future directions.

A bibliometric analysis of inverse optimization

This paper presents an overview of inverse optimization through a bibliometric approach. The goal of this study was to discover research trends and knowledge growth in the field of inverse optimization. We collected the most cited articles and documents related to the topic in the SCOPUS database. We analyzed and conducted bibliometric analyses, such as citation analysis, publication counts, and co-occurrence analysis on top articles, authors, countries, institutions, and journals, using the VOSviewer software. The results of our analyses are presented as comprehensive network maps, in which we can identify the previous and current publication trends as well as forecast future publishing trends, in the context of inverse optimization.

Drivers of Nutritional Change in Pakistan: A Decomposition Analysis.

The global reduction in child undernutrition highlights the international and national commitment to prioritizing future generations' health. This study aims to find out the previous trends in nutrition and the key drivers of these changes in different regions of Pakistan. For empirical investigation, we employed a regression-based decomposition model by using two distinct rounds of demographic and health surveys: 2012-13 and 2017-18. Results showed children with stunted growth reduced substantially in Balochistan, while Punjab exhibited the highest progress for underweight children. Regression estimates showed that maternal nutritional status and household wealth were more pronounced in reducing all measures of child malnutrition. Some determinants, including mother age at marriage and prenatal visits to the hospital, are significant only for long-term nutritional status-stunting, while mother education contributed to reducing wasted and underweight children. The rest of the factors, like father education and household environment, appear to play a humble role in explaining nutritional improvements. From disaggregated analysis based on different regions, we found that modeled factors used in this study explained changes disproportionately. Thus, it is recommended to use multidimensional nutrition policies incorporating a broader range of sectors, and region-specific programs should be designed for more effective outcomes.

Novel Association of Blunt Cerebrovascular Injuries with the San Diego–Mexico Border Wall Height Extension

The San Diego-Mexico border wall height extension is associated with increased traumatic injuries and related costs after wall falls. We report previous trends and a neurological injury type not previously associated with border falls: blunt cerebrovascular injuries (BCVIs). In this retrospective cohort study, patients who presented to the UC San Diego Health Trauma Center for injuries from border wall falls from 2016 to 2021 were considered. Patients were included if they were admitted before (January 2016 to May 2018) or after (January 2020 to December 2021) the height extension period. Patient demographics, clinical data, and hospital stay data were compared. We identified 383 patients, 51 (68.6% male; mean age, 33.5 years) in the pre-height extension cohort and 332 (77.1% male; mean age, 31.5 years) in the post-height extension cohort. There were 0 and 5 BCVIs in the pre- and post-height extension groups, respectively. BCVIs were associated with increased injury severity scores (9.16 vs. 31.33; P < 0.001), longer intensive care unit lengths of stay (median, 0 days; [interquartile range (IQR), 0-3 days]; vs. median, 5 days [IQR, 2-21 days]; P= 0.022), and increased total hospital charges (median, $163,490 [IQR,$86,578-$282,036]; vs. median, $835,260 [IQR, $171,049-$1,933,996]; P= 0.048). Poisson modeling found BCVI admissions were 0.21 (95% confidence interval, 0.07-0.41; P= 0.042) per month higher after the height extension. We review the injuries correlating with the border wall extension and reveal an association with rare, potentially devastating BCVIs that were not seen before the border wall modifications. These BCVIs and associated morbidity shed light on the trauma increasingly found at the southern U.S. border, which could be informative for future infrastructure policy decisions.

Customer Friendly Cab Booking System

Abstract: The explosive surge in demand for cabs and taxi services in comparison to public transportation owing to its convenience and safety have recently led to the invention of Internet based methods of booking private transportation. These methods of cab reservation and booking have been revolutionized with the release of internet applications which enable customers to choose among a variety of options with even access and confirmation of the booking in mere seconds. Owing to the wide fame of these applications and competition among the drivers and the different cab booking applications is one of the biggest issues. The major reason for a passenger to prefer one app over the other is the affordability and the reasonability of the suggested costs per trip. Majority of the current cab booking mobile applications in India, use some values of variables defined by the user while booking a cab, according to which the algorithm decides on a fare and chooses a driver. While most present cab booking software use some specific varying variables, a novel approach of using only the distance between the driver and passenger is chosen, the rest of the variables are optional while suggesting a driver. The results produced by this novel method will not be highly customer-defined variables-specific, it will be subject to change base only on the distance. Previous trends in consumerism of cab booking software’s and applications have been studied on the basis of research published in multiple peerreviewed journals. The idea suggests how instead of allowing only the algorithm-selected option, what advantages the concept of leaving the choice up to the customer and the driver would have, with only an optional suggestion given by the algorithm. It is programmed to optimize both end users’ experience while at the same time providing a certain amount of profit to the software owning company and the driver while still catering to the passenger’s expectations in terms of safety, comfort and speed of response. The proposed solution will help us to compare the prices between different cab booking applications like Uber and Ola which are majorly used by the consumers in India for cab booking. This idea would tackle the problem of having multiple applications for cab booking since the customer will not have to switch between multiple applications. This is a one stop solution which will compare the booking prices offered by different cab booking applications, the user will be able to choose the best, fair and cheapest cab option for their journey.

United States politicians’ tone became more negative with 2016 primary campaigns

There is a widespread belief that the tone of political debate in the US has become more negative recently, in particular when Donald Trump entered politics. At the same time, there is disagreement as to whether Trump changed or merely continued previous trends. To date, data-driven evidence regarding these questions is scarce, partly due to the difficulty of obtaining a comprehensive, longitudinal record of politicians’ utterances. Here we apply psycholinguistic tools to a novel, comprehensive corpus of 24 million quotes from online news attributed to 18,627 US politicians in order to analyze how the tone of US politicians’ language as reported in online media evolved between 2008 and 2020. We show that, whereas the frequency of negative emotion words had decreased continuously during Obama’s tenure, it suddenly and lastingly increased with the 2016 primary campaigns, by 1.6 pre-campaign standard deviations, or 8% of the pre-campaign mean, in a pattern that emerges across parties. The effect size drops by 40% when omitting Trump’s quotes, and by 50% when averaging over speakers rather than quotes, implying that prominent speakers, and Trump in particular, have disproportionately, though not exclusively, contributed to the rise in negative language. This work provides the first large-scale data-driven evidence of a drastic shift toward a more negative political tone following Trump’s campaign start as a catalyst. The findings have important implications for the debate about the state of US politics.

Organization Life Cycle and Key Methods of Enterprise Development in Current Practice of Management

While analyzing organization life cycle, stages of development and slump the article found out that the stage of restoration is similar to the stage of start, but it differs from the latter, as a new spiral of enterprise life cycle is formed with regard to previous developments, experience and work trends. After SWOT-analysis the necessity to use strategies of the pretender to leadership on market is assessed. Estimation of weak sides showed that the absence of advert materials for a store with a limited geography cannot foster successful product promotion. The simplest way to attract customers is to use social nets. Estimation of opportunities focuses on studying the product range. By comparing different products within one category of goods we can understand what is profitable to buy and which products should be rejected. The enterprise can increase profit, if it changes the product range, raises the purchase of popular positions and rejects illiquid goods. The mentioned indicators show that the enterprise being analyzed is competitive and acts as an active participant on market. Today its key goal is to expand market. The author underlines the importance of using measures aiming at changing enterprise life cycle stages with the help of tools of digital economy.

Difference in impact on emergency department visits following four major peaks of COVID-19 cases

Objective: Several variants of SARS-CoV-2 have emerged since its first appearance in 2019, greatly impacting healthcare systems across the globe. Previous literature indicated a substantial decline in emergency department (ED) visits in hospitals since the start of the COVID-19 pandemic. However, little research has been done to compare different variants’ (Ancestral, Alpha, Delta, Omicron, etc.) impact on patients presenting to the ED. Thus, the purpose of this retrospective observational study is to compare the changes in total ED volume following four major peaks of SARS-CoV-2 infection within a multi-hospital health system.Methods: Utilizing electronic healthcare record (EHR) data, total ED visits (484,268) and COVID-19 case counts (24,358) were collected and analyzed to compare ED census and COVID-19 trends across four years and four variant peak periods, from January 2019 to June 2022.Results: Results showed that ED visits declined after the first two major peaks (Ancestral and Alpha) in COVID-19 cases, which was consistent with national trends and prevailing literature. In contrast, ED visits increased following the fourth major peak (Omicron) in COVID-19 cases.Conclusions: The increase in ED visits following the fourth major peak was inconsistent with previous literature and trends. This may be attributed to the severity differences between variants, increased vaccination uptake, newly adopted public countermeasures, and evolving perceptions of safety and fear regarding COVID-19. These results underscore the critical importance for health administrators and policy planners to be cognizant of new strategies that alleviate barriers to receiving emergency care, especially during times of crisis.

Techniques for Stock Market Prediction: A Review

Stock market forecasting has long been viewed as a vital real-life topic in economics world. There are many challenges in stock market prediction systems such as the Efficient Market Hypothesis (EMH), Nonlinearity, complex, diverse datasets, and parameter optimization. A stock's value on the stock market fluctuates due to many factors like previous trends of the stock, the current news, twitter feeds, any online customer feedbacks etc. In this paper, the literature is critically analysed on approaches used for stock market prediction in terms of stock datasets, features used, evaluation metrics used, statistical, machine learning and deep learning techniques along with the directions for the future. The focus of this review is on trend and value prediction for stocks. Overall, 68 research papers have been considered for review from years 1998-2023. From the review, Indian stock market datasets are found to be most frequently used datasets. Evaluation metrics used commonly are accuracy and Mean Absolute Percentage Error. ARIMA is reported as the most used frequently statistical technique for stick market prediction. Long-Short Term Memory and Support Vector Machine are the commonly used algorithms in stock market prediction. The advantages and disadvantages of frequently used evaluation metrics, machine learning, deep learning and statistical approaches are also included in this survey.

Dispute Resolution in Indonesian Islamic Banking: Previous Trends and Future Perspectives

Currently, the legal environment for dispute resolution in the Islamic banking industry in Indonesia is not sufficient to achieve the main purpose of establishing a bank. Although Islamic legal frameworks are important for resolving financial disputes recognized under classical Islamic law, this paper aims to overcome increasing disputes as Islamic banking revenues increase. , provides arguments and solutions for resolving Islamic banking disputes using the Engel curve theory of microeconomics. Therefore, changes in the income of Islamic banks in Indonesia do not significantly affect changes in alternative dispute resolution/ADR requests. Even if the demand for ADR continues to grow, the demand for ADR will be relatively smaller than the change in Islamic banking earnings. The legal framework is dispute resolution in the Islamic banking industry based on the alternative dispute resolution (ADR) process that Prophet Muhammad has demonstrated since his stay in Medina. Conclusion; With this in mind, the Islamic banking services industry is saved from litigation domination that always comes with negative stereotypes about unnecessary payments.

Dispute Resolution in Indonesian Islamic Banking: Previous Trends and Future Perspectives

Dispute Resolution in Indonesian Islamic Banking: Previous Trends and Future Perspectives

Trends in depression risk before and during the COVID-19 pandemic.

Using 11 years of the U.S. Centers for Disease Control and Prevention (CDC) Behavioral Risk Factor Surveillance System survey data set for 2011 to 2021, we track the evolution of depression risk for U.S. states and territories before and during the COVID-19 pandemic. We use these data in conjunction with unemployment and COVID case data by state and by year to describe changes in the prevalence of self-reported diagnosis with a depressive disorder over time and especially after the onset of COVID in 2020 and 2021. We further investigate heterogeneous associations of depression risk by demographic characteristics. Regression analyses of these associations adjust for state-specific and period-specific factors using state and year-fixed effects. First, we find that depression risk had been increasing in the US in years preceding the pandemic. Second, we find no significant average changes in depression risk at the onset of COVID in 2020 relative to previous trends, but estimate a 3% increase in average depression risk in 2021. Importantly, we find meaningful variation in terms of changes in depression risk during the pandemic across demographic subgroups.

Estimates of Golf-Related Upper Extremity Injuries in the United States: A 10-Year Epidemiology Study (2011-2020).

Golf is one of the most popular sports in the United States (US) and is played by participants of all ages and skill level. Given the popularity and sport-specific demands on the upper torso, golf poses a considerable risk for upper extremity (UE) injuries. Therefore, the aim of the current study was to (1) determine the incidence rate of UE golf injuries presenting to emergency departments (EDs) in the US, (2) determine the most commonly injured body parts and mechanisms of injury, and (3) compare current injury epidemiology with previous trends in the literature. Male sex, bimodal age extremes (young and elderly), and utilization of golf carts (vs walking) are associated with a higher incidence of golf-related UE injuries. Descriptive epidemiology study. Level 3. The National Electronic Injury Surveillance System (NEISS) is a statistically validated injury surveillance system that collects data from ED visits as a representative probability sample of hospitals in the US. We queried the NEISS for the years 2011 to 2020 to examine the following variables for golf-related UE injuries: sociodemographic, diagnosis, body part, and mechanism of injury. From 2011 to 2020, there were a total of 1862 golf-related UE injuries presenting to participating EDs, which correlates to an estimated 70,868 total injuries. Overall, male golf players were disproportionately affected (69.2%) versus female golf players (30.8%) and the most commonly injured age groups were those aged >60 and 10 to 19 years. The most common injuries included fractures (26.8%), strains/sprains (23.4%), and soft tissue injuries (15.9%). The joints injured most frequently were the shoulder (24.8%), wrist (15.6%), and joints in the hand (12.0%). The most common mechanisms of injury were cart accidents (44.63%), falling/tripping (29.22%), and golf club swinging/mechanics (10.37%). Golf-related UE injuries can be acute or due to chronic overuse. Male athletes >60 years of age were the population most commonly presenting to the ED with a golf-related injury. Further, the shoulder, forearm, and wrist were most commonly injured. These findings are consistent with previous epidemiological trends in the literature. Interventions to reduce the incidence of injury should be sport-specific and focus primarily on equipment and golf cart safety and swing modification to optimize the biomechanical function of the UEs. Our findings indicate that golf-related injury prevention programs should target UE injuries, particularly among young (<19) and older (>60 years) golfers with poor swing mechanics.

Trends in Depressive Symptoms and Suicidality of South Korean Adolescents: Comparison of Expected and Observed Prevalence During the COVID-19 Pandemic

PurposeDepressive symptoms and suicidality of adolescents during the COVID-19 pandemic are emerging public health issues. However, there is a lack of representative studies on adolescents' mental health that considers the preceding secular trends. MethodsThis descriptive study used nationally representative cross-sectional data of Korean adolescents from the Korea Youth Risk Behavior Survey from 2005 to 2020 (N = 1,035,382). We utilized joinpoint regression analysis to explore the temporal prevalence trends of depressive symptoms, suicidal ideation, and suicide attempts. Based on the annual percentage change until 2019, the expected and actual prevalence in 2020 (N = 54,948) was compared to describe departures of prevalence from the trend line. These trends between sex, school level, ethnic status, and socioeconomic status were also compared. ResultsConsidering the recent increase in secular trends until 2019, the actual observed values in 2020 were lower than expected by 13% in depressive symptoms, 20% in suicidal ideation, and 40% in suicide attempts. The gap between sexes, school levels, ethnic status, and socioeconomic groups was similar or narrowed in 2020 compared to previous trends. DiscussionWe observed a lower prevalence of depressive symptoms and suicidality among Korean adolescents than expected about 9 months from the beginning of the COVID-19 pandemic despite the recent increase in secular trends.