8 research outputs found
The Impact of COVID-19 on Physical (In)Activity Behavior in 10 Arab Countries.
Insufficient physical activity is considered a strong risk factor associated with non-communicable diseases. This study aimed to assess the impact of COVID-19 on physical (in)activity behavior in 10 Arab countries before and during the lockdown. A cross-sectional study using a validated online survey was launched originally in 38 different countries. The Eastern Mediterranean regional data related to the 10 Arabic countries that participated in the survey were selected for analysis in this study. A total of 12,433 participants were included in this analysis. The mean age of the participants was 30.3 (SD, 11.7) years. Descriptive and regression analyses were conducted to examine the associations between physical activity levels and the participants\u27 sociodemographic characteristics, watching TV, screen time, and computer usage. Physical activity levels decreased significantly during the lockdown. Participants\u27 country of origin, gender, and education were associated with physical activity before and during the lockdown (p \u3c 0.050). Older age, watching TV, and using computers had a negative effect on physical activity before and during the lockdown (p \u3c 0.050). Strategies to improve physical activity and minimize sedentary behavior should be implemented, as well as to reduce unhealthy levels of inactive time, especially during times of crisis. Further research on the influence of a lack of physical activity on overall health status, as well as on the COVID-19 disease effect is recommended
Sex disparities in food consumption patterns, dietary diversity and determinants of self-reported body weight changes before and amid the COVID-19 pandemic in 10 Arab countries
The COVID-19 pandemic along with its confinement period boosted lifestyle modifications and impacted women and men differently which exacerbated existing gender inequalities. The main objective of this paper is to assess the gender-based differentials in food consumption patterns, dietary diversity and the determinants favoring weight change before and amid the COVID-19 pandemic among Arab men and women from 10 Arab countries. A cross-sectional study was conducted based on a convenience sample of 12,447 households\u27 family members (mean age: 33.2 ± 12.9; 50.1% females) and information from participants aged 18 years and above was collected about periods before and during the pandemic. Findings showed that, during the COVID-19 period, the dietary diversity, declined by 1.9% among females compared to males (0.4%) (p \u3c 0.001) and by 1.5% among overweight participants (p \u3c 0.001) compared to their counterparts. To conclude, gender-sensitive strategies and policies to address weight gain and dietary diversity during emergent shocks and pandemics are urgently needed in the region
The Impact of COVID-19 on Physical (In)Activity Behavior in 10 Arab Countries
Insufficient physical activity is considered a strong risk factor associated with non-communicable diseases. This study aimed to assess the impact of COVID-19 on physical (in)activity behavior in 10 Arab countries before and during the lockdown. A cross-sectional study using a validated online survey was launched originally in 38 different countries. The Eastern Mediterranean regional data related to the 10 Arabic countries that participated in the survey were selected for analysis in this study. A total of 12,433 participants were included in this analysis. The mean age of the participants was 30.3 (SD, 11.7) years. Descriptive and regression analyses were conducted to examine the associations between physical activity levels and the participants' sociodemographic characteristics, watching TV, screen time, and computer usage. Physical activity levels decreased significantly during the lockdown. Participants' country of origin, gender, and education were associated with physical activity before and during the lockdown (p < 0.050). Older age, watching TV, and using computers had a negative effect on physical activity before and during the lockdown (p < 0.050). Strategies to improve physical activity and minimize sedentary behavior should be implemented, as well as to reduce unhealthy levels of inactive time, especially during times of crisis. Further research on the influence of a lack of physical activity on overall health status, as well as on the COVID-19 disease effect is recommended. 2022 by the authors.Scopu
Sex disparities in food consumption patterns, dietary diversity and determinants of self-reported body weight changes before and amid the COVID-19 pandemic in 10 Arab countries
Background: The COVID-19 pandemic along with its confinement period boosted lifestyle modifications and impacted women and men differently which exacerbated existing gender inequalities. The main objective of this paper is to assess the gender-based differentials in food consumption patterns, dietary diversity and the determinants favoring weight change before and amid the COVID-19 pandemic among Arab men and women from 10 Arab countries.
Methods: A cross-sectional study was conducted based on a convenience sample of 12,447 households' family members (mean age: 33.2 ± 12.9; 50.1% females) and information from participants aged 18 years and above was collected about periods before and during the pandemic.
Results: Findings showed that, during the COVID-19 period, the dietary diversity, declined by 1.9% among females compared to males (0.4%) (p < 0.001) and by 1.5% among overweight participants (p < 0.001) compared to their counterparts.
Conclusions: To conclude, gender-sensitive strategies and policies to address weight gain and dietary diversity during emergent shocks and pandemics are urgently needed in the region.This research was funded by the Research Foundation Flanders (G047518N) and Flanders Innovation and Entrepreneurship (HBC.2018.0397). These funding sources had no role in the design of the study, the analysis and interpretation of the data or the writing, nor the decision to publish the manuscript.Scopu
Sex disparities in food consumption patterns, dietary diversity and determinants of self-reported body weight changes before and amid the COVID-19 pandemic in 10 Arab countries
info:eu-repo/semantics/publishe
Impact of COVID-19 lockdown on smoking (waterpipe and cigarette) and participants' BMI across various sociodemographic groups in Arab countries in the Mediterranean Region
Introduction
Tobacco smokers are at high risk of developing severe COVID-19.
Lockdown was a chosen strategy to deal with the spread of infectious diseases;
nonetheless, it influenced people’s eating and smoking behaviors. The main
objective of this study is to determine the impact of the COVID-19 lockdown
on smoking (waterpipe and cigarette) behavior and its associations with
sociodemographic characteristics and body mass index.
Methods
The data were derived from a large-scale retrospective cross-sectional
study using a validated online international survey from 38 countries (n=37207)
conducted between 17 April and 25 June 2020. The Eastern Mediterranean Region
(WHO-EMR countries) data related to 10 Arabic countries that participated in this
survey have been selected for analysis in this study. A total of 12433 participants
were included in the analysis of this study, reporting their smoking behavior and
their BMI before and during the COVID-19 lockdown. Descriptive and regression
analyses were conducted to examine the association between smoking practices
and the participant’s country of origin, sociodemographic characteristics, and
BMI (kg/m 2 ).
Results
Overall, the prevalence rate of smoking decreased significantly during
the lockdown from 29.8% to 23.5% (p<0.05). The percentage of females who
smoke was higher than males among the studied population. The highest smoking
prevalence was found in Lebanon (33.2%), and the lowest was in Oman (7.9%).
In Egypt, Kuwait, Lebanon, and Saudi Arabia, the data showed a significant
difference in the education level of smokers before and during the lockdown
(p<0.05). Smokers in Lebanon had lower education levels than those in other
countries, where the majority of smokers had a Bachelor’s degree. The findings
show that the BMI rates in Jordan, Lebanon, Oman, and Saudi Arabia significantly
increased during the lockdown (p<0.05). The highest percentages of obesity
among smokers before the lockdown were in Oman (33.3%), followed by Bahrain
(28.4%) and Qatar (26.4%), whereas, during the lockdown, the percentage of
obese smokers was highest in Bahrain (32.1%) followed by Qatar (31.3%) and
Oman (25%). According to the logistic regression model, the odds ratio of smoking
increased during the pandemic, whereas the odds ratio of TV watching decreased.
This finding was statistically significant by age, gender, education level, country
of residence, and work status.
Conclusions
Although the overall rates of smoking among the studied countries
decreased during the lockdown period, we cannot attribute this change in smoking behavior to the lockdown. Smoking cessation services need to anticipate that
unexpected disruptions, such as pandemic lockdowns, may be associated with
changes in daily tobacco consumption. Public health authorities should promote
the adoption of healthy lifestyles to reduce the long-term negative effects of the
lockdown
Machine learning techniques for the identification of risk factors associated with food insecurity among adults in Arab countries during the COVID-19 pandemic
Abstract Background A direct consequence of global warming, and strongly correlated with poor physical and mental health, food insecurity is a rising global concern associated with low dietary intake. The Coronavirus pandemic has further aggravated food insecurity among vulnerable communities, and thus has sparked the global conversation of equal food access, food distribution, and improvement of food support programs. This research was designed to identify the key features associated with food insecurity during the COVID-19 pandemic using Machine learning techniques. Seven machine learning algorithms were used in the model, which used a dataset of 32 features. The model was designed to predict food insecurity across ten Arab countries in the Gulf and Mediterranean regions. A total of 13,443 participants were extracted from the international Corona Cooking Survey conducted by 38 different countries during the COVID -19 pandemic. Results The findings indicate that Jordanian, Palestinian, Lebanese, and Saudi Arabian respondents reported the highest rates of food insecurity in the region (15.4%, 13.7%, 13.7% and 11.3% respectively). On the other hand, Oman and Bahrain reported the lowest rates (5.4% and 5.5% respectively). Our model obtained accuracy levels of 70%-82% in all algorithms. Gradient Boosting and Random Forest techniques had the highest performance levels in predicting food insecurity (82% and 80% respectively). Place of residence, age, financial instability, difficulties in accessing food, and depression were found to be the most relevant features associated with food insecurity. Conclusions The ML algorithms seem to be an effective method in early detection and prediction of food insecurity and can profoundly aid policymaking. The integration of ML approaches in public health strategies could potentially improve the development of targeted and effective interventions to combat food insecurity in these regions and globally