Background: The delivery mode is one of the factors affecting the type of colonization of the human gut. Gut colonization affects all stages of the human life cycle, and the type of gut microbiome can contribute to immune system function, the development of some diseases, and brain development; and it has a significant impact on a newborn’s growth and development. Methods: Terms defined as MeSH keywords were searched by the databases, and web search engines such as PubMed, ClinicalTrials.gov, Embase, Scopus, ProQuest, Web of Science, and Google Scholar were searched between 2010 and 2020. The quality of each study was assessed according to the Newcastle–Ottawa scale, and seven eligible and high-quality studies were analyzed. Finding: The abundances of Bacteroides and Bifidobacterium during the first 3 months of life; Lactobacillus and Bacteroides during the second 3 months of life; Bacteroides and Bifidobacterium during the second 6 months of life; and Bacteroides, Enterobacter, and Streptococcus after the first year of life were higher in vaginal delivery-born infants. While infants born by cesarean section (CS) had higher abundances of Clostridium and Lactobacillus during the first 3 months of life, Enterococcus and Clostridium during the second 3 months of life, and Lactobacillus and Staphylococcus after the first year of life. Discussion: Delivery mode can affect the type of the human intestinal microbiota. The CS-born babies had lower colonization rates of Bifidobacterium and Bacteroides, but they had higher colonization rates of Clostridium, Lactobacillus, Enterobacter, Enterococcus, and Staphylococcus. Given the effect of microbiota colonization on neonatal health, it is therefore recommended to conduct further studies in order to investigate the effect of the colonization on the delivery mode and on baby’s growth and development. Application to practice: The aim of this study was to investigate the role of CS in the development of the neonatal gut microbiota.

Purpose: There are few studies on the gender differences in mental health, happiness, and their related factors among the older population through the structural equation model (SEM) in Iran. We conducted this study to evaluate the factors affecting mental health and happiness in the elderly using an SEM by gender differences.Methods: A cross‐sectional study was conducted on 739 elderly people in 2019 in Karaj, Iran. Sociodemographic, Symptom Checklist‐90‐Revised (SCL90‐R), and the Oxford Happiness Inventory were applied to evaluate the relationships between happiness, mental health, and sociodemographic factors by using statistical path analysis with Lisrel 8.8 and SPSS‐17.Results: Overall, 55.5% of the participants in the study were female. The SCL90 (p value = .000) and happiness (p value = .000) scores showed significant differences between men and women. Fit indices confirmed the high model fitness, desirability, and logical relationships between the variables according to the conceptual model in both men (X2 = 3.2, df = 1) and women (X2 = 5.4, df = 2) groups. According to the path analysis, among the variables that affected happiness just through the direct path, education had the most positive causal relationship in men (B = .13) and women (B = .16), but mental health problems in men (B = −.33) and women (B = −.26), as well as the distance from home to the healthcare center in men (B = −.13) and women (B = −.11), had the most negative causal relationship with happiness respectively. Age was the only variable that was negatively related to happiness through direct and indirect paths in the women (B = −.188).Conclusion: We provided an empirical model that illustrates the relationships between happiness, mental health, and related factors in the older population. Gender differences in path analysis showed that age negatively affects the happiness of older women but not men.

Considering the importance of long COVID-19 (LC), this study aimed to investigate the relationship between clinical/sociodemographic factors and LC symptoms (LCS). This online cross-sectional study was conducted on 308 people infected with COVID-19 in Alborz, Iran, from April 1 to June 1, 2022. Multivariable logistic regression models were applied to measure the association between the LCS with other variables. Overall, 76.6% of participants had at least one LCS. Results from the multivariate logistic regression analysis showed that females (crude odds ratio [OR] [95% confidence interval (CI)]: 2.725 [1.42, 5.22]), educated persons (3.747 [1.58, 8.84]), people with a higher number of COVID-19 reinfection (2.280 [1.30, 3.97]), having an underlying disease (1.996 [1.01, 3.93]), and COVID-19 severity (3.321 [1.037, 10.635]) had higher odds of LC than others (all p < .05). Study findings provide additional clinical/sociodemographic data on risk for LC. These data may inform future research and clinical practice for potential risk identification and early intervention.

Background: Self-management behaviors can reduce the progression of an illness. Although various factors affect self-management, no study has been conducted on the self-management of tuberculosis (TB) through path analysis.Objectives: This study evaluated the factors affecting self-management in TB patients using path analysis.Methods: A cross-sectional study was done on 133 non-prisoner TB patients that referred to all health centers in Karaj, Iran, in 2017. A structured questionnaire was applied. Data were analyzed with SPSS-17 and Lisrel 8.8, utilizing statistical path analysis to evaluate the relationships between self-management and its related factors. Results: Overall, 52.3% of the participants in the study were female and 47.7% were male. Respondents of were 46.9% smear-positive, 9.4% smear-negative, and 43.8% extra-pulmonary TB. Fit indices confirmed the model fitness and logical relationships between the variables according to the conceptual model (chi 2 = 49.80, df = 25). The final path model showed that age (/ = 0.84), attitude (/ = 0.10), marital status (/ = 0.04), and house condition (/ = 0.03) impact self-management through the direct path. Knowledge (/ = 0.83) and education (/ = 0.16) affect self-management through both direct and indirect paths. Education indirectly affects self-management through both knowledge and attitude. Knowledge indirectly impacts self-management through attitude. In other words, knowledge and attitude mediate the relationship between some factors and self-management.Conclusions: This study provided an empirical model that illustrates the relationships between self-management and related factors in TB patients. The knowledge can be the target of interventions in support of self-management.

Background: The COVID-19 pandemic has created significant challenges in 2020 in the world and Iran. To help vulnerable groups such as refugees during the response and recovery phases of the COVID-19 pandemic, identifying the quality of life (QOL) and its associated factors is helpful. Considering that research in this field is limited, this study evaluated the effect of social determinants of health on the quality of life among Afghan refugees in Iran during the COVID-19 pandemic. Methods: We conducted a cross-sectional study on 300 Afghan refugees and migrants in Alborz province, Iran, from February to May 2022 using Convenience sampling. Data were completed using the socioeconomic status scale (SES), World Health Organization's quality of life -BREF (WHOQOL), Depression, Anxiety and Stress Scale—21 Items (DASS-21), and COVID-19 Post-Traumatic Stress Disorder Checklist (COVID-PTSD). In addition, path analysis was applied to evaluate the relationships among the research variables with quality of life. Results: 64.3% of the study participants were male, with a mean of 29.29 ± 9.64 years. The path analysis showed that SES had the most positive relationship (B = .266), and the number of COVID-19 cases had the most negative relationship (B = -.169) with the quality of life from both paths. The self-rated health had the most positive relationship (B = .25), and the DASS score had the most negative relationship (B = -.2) with the quality of life through only one path. Access to medical services was the only variable that indirectly had a positive causal relationship with QOL (B = .044). Conclusion: We provided an empirical model that illustrates the relationships between quality of life and social determinants of health among Afghan refugees and migrants during the Covid19 pandemic. The negative emotional states of Depression, Anxiety, and Stress (DAS) as a mediator play an essential role in the quality of life and other variables.

Background: Pregnancy and motherhood are very valuable but challenging for women with multiple sclerosis (MS). Given that there are limited studies in this field, this study aimed to determine the social determinants of health on attitudes toward childbearing among women with MS.Methods: We conducted a cross‐sectional study on 206 women with MS in Alborz province, Iran, from February to June 2023 using convenience sampling. The data were collected using the questionnaire, and a linear regression analysis was applied.Results: The mean age of the participants was 36.80 ± 6.50 years. Participants’ Attitudes toward Fertility and Childbearing (PAFC) had a positive significant association with social support (B = .10, SE = .04, p = .023) and a significant negative association with the total score of depression, anxiety, and stress scale (B = −.13, SE = .06, p = .047) and depression (B = −.40, SE = .18, p = .023). However, the association between anxiety (B = −.25, SE = .20, p = .211), stress (B = −.36, SE = .18, p = .050), MS severity (B = .04, SE = .30, p = .890), and socioeconomic status scale (SES) (B = −.08, SE = .32, p = .806) was nonsignificant with PAFC.Conclusion: Our results showed that factors, including social support and mental health especially depression, can affect PAFC in women with MS. Therefore, it is necessary to determine specific strategies for policymakers to help MS patients manage pregnancy and motherhood.