Prevalence and factors associated with depression, anxiety and stress symptoms among construction workers in Nepal.

IntroductionThe construction industry in Nepal, which employs a significant proportion of the population, ranks as one of the largest industries in the country. Construction work is physically demanding and can be risky due to the use of heavy machinery and the presence of intense physical labor. However, the physical and mental health of construction workers in Nepal is often neglected. This study aimed to assess psychological distress (depression, anxiety, and stress symptoms) and its association with socio-demographic, lifestyle, and occupational factors among construction workers in Kavre district, Nepal.MethodsWe conducted a cross-sectional study from 1st October 2019 to 15th January 2020 among 402 construction workers in Banepa, and Panauti municipalities of Kavre district, Nepal. We collected data with face-to-face interviews using a structured questionnaire consisting of a) socio-demographic characteristics; b) lifestyle and occupational characteristics; and c) depression, anxiety and stress symptoms. We collected data using electronic forms in KoboToolbox and imported them into R version 3.6.2 for statistical analysis. We present parametric numerical variables as mean and standard deviation, and categorical variables as percentage and frequency. The confidence interval around proportion was estimated with the Clopper-Pearson method. We applied univariate and multivariable logistic regression to determine factors associated with depression symptoms, anxiety, and stress. The result of logistic regression was presented as crude odds ratio, adjusted odds ratio (AOR), and their 95% confidence interval (CI).ResultsThe prevalence of depression, anxiety and stress symptoms were 17.1% (95%CI: 13.6-21.2), 19.2% (95%CI: 15.5-23.4) and 16.4% (95%CI: 12.9-20.4), respectively. In multivariable logistic regression analysis, depression symptom was positively associated with poor sleep quality (AOR = 3.51; 95%CI: 1.5-8.19; p-value: 0.004); stress symptom was positively associated with Brahmin ethnicity (AOR = 3.76; 95%CI:1.34-10.58; p-value: 0.012) and current smoking (AOR = 2.0; 95%CI: 1.11-3.82 p-value: 0.022). But anxiety symptoms were not associated with any of the variables.ConclusionsThe prevalence of depression, anxiety, and stress symptoms were high among construction workers. Developing evidence-based and appropriate community-based mental health prevention programs among laborers and construction workers is recommended

Management of health information of nepalese labour migrants

Abstract Introduction The monitoring and improvement of the health of labour migrants (LMs) require sufficient health data to be recorded and managed. In this context, this study was conducted to explore the management of health information of Nepalese labour migrants (NLMs). Methods This is an explorative qualitative study. Stakeholders involved directly or indirectly in maintaining the health profile of NLMs were first mapped, physically visited, and any documents or information were collected. Then, sixteen key informant interviews were conducted among these stakeholders related to labour migrants’ health information management and challenges. A checklist extracted information from the interviews, and a thematic analysis was carried out to summarize the challenges. Results Government agencies, non-governmental organizations, and government approved private medical centers are involved in generating and maintaining the health data of NLMs. The Foreign Employment Board (FEB) records deaths and disabilities of NLMs while at work abroad and these health records are also maintained in an online portal called Foreign Employment Information Management System (FEIMS) under the Department of Foreign Employment (DoFE). Health assessment of NLMs is a mandatory procedure before departure, which is done through the government-approved pre-departure private medical assessment centers. The health records from these assessment centers are first recorded in paper-based form and then entered into an online electronic form to be stored by the DoFE. The filled-up paper forms are sent to District Health Offices, which further report the data to the Department of Health Services (DoHS), Ministry of Health and Population (MoHP) and associated governmental infectious diseases centers. However, there is no formal health assessment of NLMs upon arrival to Nepal. Key informants raised various issues and concerns in maintaining health records of NLMs, which were grouped into three themes: lack of interest to develop a unified online system; need of competent human resources and equipment; and developing a set of health indicators for migrant health assessment. Conclusion The FEB and government-approved private assessment centers are the main stakeholders in keeping the health records of outgoing NLMs. The current migrant health record keeping procedure in Nepal is fragmented. The national Health Information Management Systems does not effectively capture and categorize the health record of NLMs. There is a need to effectively link national health information system with premigration health assessment centers; and potentially develop a migrant health information management system by systematically keeping health records electronically with relevant health indicators on departing and arriving NLMs

Academic Stress among Adolescents of Rural Nepal: A Community-based Cross-Sectional Study

Background: Adolescents are in the transition phase between childhood and adulthood. Their mental health influences many aspects in their life as they go through many physical and emotional changes. Adolescent mental health is harmed by changes in emotional and physical state, as well as increased academic pressure. This study aimed to assess academic stress and its associated factors among adolescents in rural Nepal. Methods: A community-based cross-sectional survey was conducted among 424 adolescents residing in Karnali Province, Nepal. Academic stress was measured using Student Assessing Academic Stress. Multivariate logistic regression analysis was used to examine associated factors at the significance level of 0.05. Results: Of the total students, 19.8% had moderate academic stress and 2.4% of them had high academic stress. Female students had thrice higher odds of having academic stress as compared to male students (Adjusted Odds Ratio:3.47; 95% Confidence Interval:1.91to 6.31, p-value:<0.001). Grade 10 students had higher odds of having academic stress as compared to grade 9 (Adjusted Odds Ratio:2.02; 95% Confidence Interval:1.13 to 3.61, p-value:0.017). Students of literate mothers were more likely to experience academic stress than those with illiterate mothers (Adjusted Odds Ratio:0.53; 95% Confidence Interval:0.29 to 0.96, p-value:0.036). Students with unsatisfactory academic performance had thrice higher odds of having academic stress as compared to students with satisfactory academic performance (Adjusted Odds Ratio:3.12; 95% Confidence Interval:1.46 to 6.67, p-value:<0.003). Conclusions: The findings of the study showed that high school students have academic stress, which is related to many factors at home and school. Understanding academic stress and parents and teachers providing the best support to the students could help lessen the burden. Keywords: Academic stress; adolescents; Nepal; prevalenc

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

BackgroundEstimates 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.Methods22 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.FindingsGlobal 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.InterpretationGlobal 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