Obesity and Mortality of Hospitalized COVID-19 Patients in Asian and Western Countries: A Systematic Review and Meta-Analysis.

Background: The authorities recently emphasized the importance of dietary control for COVID-19 patients in hospitals. However, there is limited detail about the obesity and death of COVID-19 patients who are hospitalized in the Asian and Western countries. The aim of this study was to find the role of obesity and mortality of the hospitalized COVID-19 patients. A systematic review of the studies on obesity and mortality of hospitalized COVID.19 patients in the Asian and western countries. Methods: Databases of ProQuest, PubMed, and EBSCO were used to find relevant articles published between January 2020 and March 2021. A total of 3,70,836 patients in 17 studies were included. Results: We found significant correlation between obesity and mortality in hospitalized COVID-19 patients (pooled odds ratio [POR] = 1.28, 95% CI: 1.23-1.33). In particular, this study demonstrated that the Asian countries had higher POR (1.44, 95% CI: 1.16-1.79) compared to the western countries (1.28, 95%CI: 1.23-1.33). The heterogeneity calculation showed heterogenous among studies included (I2 > 50%). Conclusions: The mortality of COVID-19-hospitalized patients is related to obesity, which requires a multi-stakeholder mitigation approach to avoid and control obesity and its impacts. Conclusions: The mortality of COVID-19-hospitalized patients is related to obesity, which requires a multi-stakeholder mitigation approach to avoid and control obesity and its impacts.

The risk factors and pregnant women's willingness toward the SARS-CoV-2 vaccination in various countries: A systematic review and meta-analysis.

INTRODUCTION: Pregnant women will benefit from research on immunization during pregnancy because they will have more accurate information on the SARS-CoV-2 vaccine. The purpose of this study was to determine the risk factors and pregnant women's desire to get the SARS-CoV-2 vaccine in various countries. METHODS: A search of PubMed, ProQuest, and EBSCO for related publications published (January and December 2021) on risk factors and pregnant women's desire to get the SARS-CoV-2 vaccine in various countries. The Pooled Odds Ratio (POR) were calculated using fixed and random-effect analysis. The I-squared formula was used to calculate the heterogeneity. Egger's and Begg's tests were used to identify study bias. STATA 16.0 was used for data analysis. RESULTS: This study revealed good practice has the highest POR (8.99), followed by received influenza vaccine last year (2.72), high perception of SARS-CoV-2 vaccine (2.70), >35 years (2.01), sufficient information about the SARS-COV-2 vaccine (1.94), higher school education (1.84), and third trimester (1.35) with pregnant women's desire toward the SARS-CoV-2 vaccination. The heterogeneity analysis revealed homogenous among risk factors in >35 years, high perception of SARS-CoV-2 vaccine, good practice, and third trimester (I2 ≤ 50%). In the articles combined in this study, there was no indication of study bias. CONCLUSION: The insights of this study might help the authorities in determining the most effective strategy to deploy SARS-CoV-2 mass immunization campaigns for pregnant women.

Acceptance of COVID-19 vaccination and correlated variables among global populations: A systematic review and meta-analysis.

INTRODUCTION: The most awaited solution is an efficient COVID-19 vaccine. COVID-19 vaccine acceptance has not been studied in a meta-analysis. The objective of this research was to find the acceptance of COVID-19 vaccination and correlated variables. METHODS: A systematic review of studies on acceptance of COVID-19 vaccination and correlated variables in the ProQuest, PubMed, and EBSCO to find relevant articles published between January 2020 and March 2021. Using fixed and random-effect models, the risk factors Pooled Odds Ratio (POR) were measured. The heterogeneity was calculated using the I-squared formula. Egger's and Begg's tests were utilised to determine publication bias. STATA 16.0 was used for all data processing and analysis. RESULTS: This study results showed the related factors for COVID-19 vaccination acceptance, high income has the highest odd ratio (POR = 2.36), followed by encountered with COVID-19 (POR = 2.34), fear about COVID-19 (POR = 2.07), perceived benefits (POR = 1.81), flu vaccine during the previous season (POR = 1.69), healtcare workers (POR = 1.62), male (POR = 1.61), married (POR = 1.59), perceived risk (POR = 1.52), trust in health system (POR = 1.52), chronic diseases (POR = 1.47), high education (POR = 1.46), high level of knowledge (POR = 1.39), female (1.39), and older age (POR = 1.07). The heterogeneity calculation showed homogenous among studies in high income, fear about COVID-19, healthcare workers, married, chronic diseases, and female (I2 ≤ 50%). For the studies included in this review, there was no apparent publication bias. CONCLUSION: The analysis of this review may be useful to the nation in determining the best method for implementing COVID-19 mass vaccination programs based on relevant factors that influence vaccine acceptance.

Dataset of Indonesian women's reproductive, high-fat diet and body mass index risk factors for breast cancer.

This dataset describes a survey presenting reproductive, high-fat diet and body mass index (BMI) determinant factors for breast cancer among Indonesian women. The information was gathered from breast cancer and non-breast cancer patients via an online questionnaire, determining reproductive factors (menarche age, menopause age, first pregnancy age, parity, and breastfeeding), high-fat diet and BMI, from 1st June until 31th September 2020. Two hundred breast cancer patients and 200 non-breast cancer patients in Indonesia willing to fill out an online survey provided the samples. The data was analyzed using IBM version 25.0, which included univariate, bivariate, and multivariate analysis. The information would help Indonesian women in identifying the potential of breast cancer.

Survey data of multidrug-resistant tuberculosis, Tuberculosis patients characteristics and stress resilience during COVID-19 pandemic in West Sumatera Province, Indonesia.

This set of data presents a survey data describing multidrug-resistant tuberculosis, tuberculosis patients characteristics and stress resilience during COVID-19 pandemic in West Sumatera Province, Indonesia. The data were gathered from multidrug-resistant tuberculosis, tuberculosis patients through a survey distributed by an online questionnaire, assesing patients characteristics (age, sex, level of education, working status, history of close contact to patients with multidrug resistant tuberculosis and tuberculosis, smoking, alcohol consumption, cavitary pulmonary, diabetes mellitus, nutritional status and tuberculosis outside the lung) and stress resilience (3 items), from 15th July until 7th August 2020. The samples were collected 73 multidrug resistant tuberculosis patients and 219 tuberculosis patients in West Sumatera Province, Indonesia who were willing to fill an online questionnaire. SPSS version 23.0 was used to analyzed the data by descriptive and inferential statistics. The data will help to identify mental health problems and potentially as a warning sign that can support for health education interventions among multidrug-resistant tuberculosis and tuberculosis patients during COVID-19 pandemic.

Survey data of COVID-19 awareness, knowledge, preparedness and related behaviors among breast cancer patients in Indonesia.

This dataset presents a survey data describing COVID-19 awareness, knowledge, preparedness and related behaviors among breast cancer patients in Indonesia. The data were collected from breast cancer patients through a survey distributed by an online questionnaire, assesing social-demographic characteristics (6 items), COVID-19 awareness (5 items), knowledge (2 items), preparedness (2 items) and related behaviors (2 items), from 20th June until 14th July 2020. The samples were gathered 500 breast cancer patients in Indonesia who were willing to fill an online questionnaire. SPSS version 23.0 was used to analyzed the data by descriptive and inferential statistics and SmartPLS 3 to created the partial least square path modeling. The data will help in preventing the transmission of COVID-19 among breast cancer patients and can support for health education and promotion interventions.