ABSTRACT
The extraordinary situation related to COVID-19 makes people worry about their health, family health, work, finances, and other daily activities. This condition can lead to social unrest, which has consequences for mental health problems. This study aims to determine the mental health consequences at the beginning of the COVID-19 pandemic in Indonesia. This is a cross-sectional study involving a target population aged 18 years and over who had access to electronic communication devices. An online questionnaire was randomly distributed and snowballed throughout 34 provinces in Indonesia. The study was conducted from 2 to 4 May 2020. Non-parametric and multivariate linear regression analyses were performed to identify factors associated with anxiety and depression. Two thousand seven hundred forty-three participants were involved in this study, with 69.16% female. In sum, 6.92% of participants had General Anxiety Disorder-7 (GAD-7) scores ≥ 10 for moderate-severe anxiety symptoms, and 8.57% had Patient Health Questionnaire-9 (PHQ-9) scores ≥ 10 for moderate-severe depressive symptoms. The multivariate linear regression analyses showed that the strongest factors influencing anxiety and depression were a history of mental illnesses, chronic illnesses, the group affected by layoffs or job seekers, unemployed, students, younger age group, living in a rented house, single, and female. In contrast, the lower and secondary education level seems to reduce the risk of depression compared to those with higher education levels. Anxiety and depression occur during the periods of activity restriction during the COVID-19 pandemic and are influenced by several modifiable and non-modifiable factors. There is an urgent need to emphasize vulnerable groups such as those with a history of illness, those affected by layoffs/looking for work, and the younger age group. © 2022, Tech Science Press. All rights reserved.
ABSTRACT
BACKGROUND: Many health workers have experienced fatigue due to high workloads with the number of patients who were confirmed positive for COVID-19 with moderate and severe symptoms who were hospitalized. Researchers identified several factors that affect the readiness of health workers in the management of COVID-19 patients, including knowledge, family status, availability of personal protective equipment (PPE), health status, and reward. Optimal self-preparation is needed to achieve COVID-19 management that is in line with expectations by examining these factors more deeply. AIM: The aim of this study was to identify and knowing factors are affect the readiness of Health personnel for COVID-19 patients’ treatment in hospital. METHODS: This research method uses a descriptive correlation design with a cross-sectional approach aimed at knowing the relationship between variables, where the independent variable and dependent variable are identified at the same time. The number of samples used as many as 34 students of the transfer class who already work as nurses in hospitals. RESULTS: There were two factors that had an influence on the readiness of transfer students in the management of COVID-19 at the hospital, namely, the family status factor and the availability of PPE with p values of 0.036 and 0.007 and three factors that had no effect, namely knowledge, health status, and giving rewards with p > 0.05. CONCLUSION: Family status and the availability of PPE become the main important factors related to readiness of health personnel for patients’ treatment in hospital. Working safely and fully support from the hospital can affect the readiness of the health workers in handling COVID-19 patients.
ABSTRACT
Changes in Body Mass Index (BMI) are the main predictors in controlling blood pressure, especially during the COVID-19 pandemic. This article aims to measure changes in BMI before and during COVID-19 for controlling obesity in hypertensive. This is a further analysis data from the Bogor Cohort Study on NCD Risk Factor and the study of the Impact of the COVID-19 Pandemic Period on Health and Mental Health Service Efforts in 2020 conducted 750 hypertension cases during 2011-2018. The dependent variable is the change in BMI which is categorized stable, decreasing, increasing based on the cut off of the mean difference in BMI. The independent variables include demographic characteristics, ownership of Health Insurance, behavior, disease status, monitoring of blood pressure, height and body weight and therapy. Data were analyzed by multinomial logistic regression. The proportion of hypertensive who experienced changes in BMI was stable, decreased and increased, respectively by 24.5 percent, 49 percent and 26.5 percent. Factors associated with changes in BMI decreased in hypertensive patients were obesity with a risk of 1.7 times (95% CI 1.1-2.6) and stress 4.8 times (95% CI 1.4-16). The factor of increased BMI changes were obesity with a protective risk of 0.6 times (95% CI 0.4-0.9), sitting more than 5.5 hours had a risk of 1.6 (95 % CI 1.1 - 2.6), and smoking >= 200 cigarettes/day has a 4.2 times risk (95% CI 1.4 - 13.0). Suggestions need efforts to maintain a stable BMI by doing physical activity, managing stress and not smoking.