Epidemic modeling and flattening the infection curve in social networks

The main goal of this paper is to model the epidemic and flattening the infection curve of the social networks. Flattening the infection curve implies slowing down the spread of the disease and reducing the infection rate via social-distancing, isolation (quarantine) and vaccination. The nan-pharmaceutical methods are a much simpler and efficient way to control the spread of epidemic and infection rate. By specifying a target group with high centrality for isolation and quarantine one can reach a much flatter infection curve (related to Corona for example) without adding extra costs to health services. The aim of this research is, first, modeling the epidemic and, then, giving strategies and structural algorithms for targeted vaccination or targeted non-pharmaceutical methods for reducing the peak of the viral disease and flattening the infection curve. These methods are more efficient for nan-pharmaceutical interventions as finding the target quarantine group flattens the infection curve much easier. For this purpose, a few number of particular nodes with high centrality are isolated and the infection curve is analyzed. Our research shows meaningful results for flattening the infection curve only by isolating a few number of targeted nodes in the social network. The proposed methods are independent of the type of the disease and are effective for any viral disease, e.g., Covid-19.Comment: in Persian language. Journal of Modelling in Engineering 202

Food and nutrition literacy status and its correlates in Iranian senior high-school students

Background: Planning interventions to promote food and nutrition literacy (FNL) require a better understanding of the FNL status of the target group and its correlates. Aims: This study aimed to examine the FNL status and its determinants in Iranian senior high-school students. Methods: In this cross-sectional study, FNL and its components (food and nutrition knowledge, functional skills, interactive skills, advocacy, critical analysis of information, and food label reading skill) were evaluated by a locally designed and validated, self-administered questionnaire. Besides, socioeconomic, demographic, anthropometric measures, as well as academic performance of 626 senior high-school students were assessed. Results: The mean ± SD of the total FNL score (within potential range of 0 to 100) was 52.1 ± 10.96, which is below the minimum adequate level of 60. The probability of high FNL knowledge score was significantly higher among students who majored in Natural Sciences (OR = 1.73, CI = 1.09�2.75), had better school performance (OR = 1.13, CI = 1.06�1.20) and higher SES score (OR = 1.20, CI = 1.01�1.44). The score for food label reading was significantly lower in girls (OR = 0.45, CI = 0.31�0.67), while those who had a family member with the nutrition-related disease were more likely to have a higher score of food label reading skill (OR = 1.48, CI = 1.01�1.64). Conclusion: The level of FNL in senior high-school students in Tehran was relatively low. These findings have key messages for the education system and curriculum designers to have more consideration for food and nutrition-related knowledge and skills in schools. © 2021, The Author(s)

Role of Physical Activity and Fitness in the Characterization and Prognosis of the Metabolically Healthy Obesity Phenotype: a Systematic Review and Meta-Analysis

The aims of the present article are to systematically review and meta-analyze the existing evidence on: 1) differences in physical activity (PA), sedentary behavior (SB), cardiorespiratory fitness (CRF) and muscular strength (MST) between metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUO); and 2) the prognosis of all-cause mortality and cardiovascular disease (CVD) mortality/morbidity in MHO individuals, compared with the best scenario possible, i.e., metabolically healthy normal-weight (MHNW), after adjusting for PA, SB, CRF or MST. Our systematic review identified 67 cross-sectional studies to address aim 1, and 11 longitudinal studies to address aim 2. The major findings and conclusions from the current meta-analysis are: 1) MHO individuals are more active, spend less time in SB, and have a higher level of CRF (yet no differences in MST) than MUO individuals, suggesting that their healthier metabolic profile could be at least partially due to these healthier lifestyle factors and attributes. 2) The meta-analysis of cohort studies which accounted for PA (N = 10 unique cohorts, 100% scored as high-quality) support the notion that MHO individuals have a 24-33% higher risk of all-cause mortality and CVD mortality/morbidity compared to MHNW individuals. This risk was borderline significant/non-significant, independent of the length of the follow-up and lower than that reported in previous meta-analyses in this topic including all type of studies, which could be indicating a modest reduction in the risk estimates as a consequence of accounting for PA. 3) Only one study has examined the role of CRF in the prognosis of MHO individuals. This study suggests that the differences in the risk of all-cause mortality and CVD mortality/morbidity between MHO and MHNW are largely explained by differences in CRF between these two phenotypes

Factors affecting sleep quality in patients with type 2 diabetes: a cross-sectional study in Iran

Abstract Background Diabetes type 2 is a chronic metabolic disease with major physical and health problems that is on the rise. The aim of this study was to evaluate the factors affecting sleep quality in patients with type 2 diabetes in Iran. This cross-sectional study was conducted on 160 patients with type 2 diabetes referred to the diabetes clinic of Kosar Hospital of Semnan city (Iran) in 2018. The sampling was convenient. The data collection tools were four questionnaires including demographic-clinical variables, Pittsburgh Sleep Quality Index (PSQI) questionnaire, Epworth Sleepiness Scale (ESS), and Beck depression inventory II questionnaire. The data was analyzed by STATA 14 and the crude and adjusted coefficient regression (β) with a 95% confidence interval (CI) were reported. Results The mean (± S.D) of age was 58.70 (± 12.16) years and 60% were female. The multivariate linear regression model showed depression (β = 0.11; 95% CI 0.07–0.16) and sex (β = 1.24; 95% CI 0.17–2.30) are the most important predictors of sleep quality in diabetic patients. However, only underlying disease (β = 1.73; 95% CI 0.33–3.12) was the most important predictors of daily sleep disorder in diabetic patients. Conclusions Depression and sex were the most important predictors of sleep quality in diabetic patients; therefore, it seems necessary to pay attention to these factors in the design of sleep disorder prevention and control programs