The Article Abstract is not available.

Background: Social health is a crucial yet underexplored dimension of human well-being, particularly in architecture and environmental design. While the links between design and physical or mental health have been widely studied, the social dimension remains insufficiently addressed. This review examines how architectural and urban design influence social health outcomes globally from 2002 to 2024. Methods: This systematic review followed the PRISMA protocol. Peer-reviewed articles were retrieved from Scopus, Web of Science, PubMed, and Google Scholar using Boolean keywords (e.g., “design*” AND “social health”). After screening 16,402 initial records, 44 studies from 14 countries and 31 journals met the inclusion criteria. Eligible studies empirically assessed environmental design factors in relation to social health indicators in real-world settings. Results: Key design features positively linked to social health include access to green and blue spaces, walkability, aesthetics, public safety, mixed land use, spatial layout, and third places. Common social outcomes were enhanced interaction, cohesion, trust, and sense of belonging. The majority of studies focused on outdoor spaces, with fewer addressing interior environments. Conclusion: The built environment significantly shapes social well-being. However, notable research gaps persist, especially in non-Western and indoor contexts. Future studies should apply mixed methods, include diverse cultural settings, and develop standardized frameworks to evaluate the social impacts of design.

Background: Comorbidity indices, such as Charlson Comorbidity Index (CCI) and Elixhauser Comorbidity Measure (ECM), are essential tools for assessing the influence of comorbid health conditions on patient outcomes. This study aims to review comorbidity indices by assigning weighted scores to a spectrum of comorbidities; these instruments play a critical role in predicting mortality rates and evaluating healthcare resource utilization. Methods: In this narrative review study, we reviewed all comorbidity indices and important points were mentioned. Results: CCIand ECIhave proven to be highly effective tools for predicting mortality and healthcare outcomes across a wide range of patient populations. This review examines four comorbidity indices: CCI, ECI, Acute Myeloid Leukemia (AML), and the Chronic Disease Index (CDI). Conclusion: Among four types, CCI and ECM were the most applied, and the researcher should know different types of comorbidity indices to use in research

Background: Previous studies indicated the risk factors for COVID-19. It is known that nutritional status is one of the main causes of immune system failure. This study aims to investigate the association of nutritional status and the outcomes of COVID-19 in participants of Yazd Health Study (YaHS). Methods: 279 people who had taken a blood test before contracting COVID-19 were included in this study in 2022. Data of PO2 level, rate of hospitalization, "supplementation with oxygen" rate, BUN, and creatinine were extracted. Hemoglobin levels and body mass index (BMI) were also evaluated. The authors applied analysis of variance (ANOVA) and independent sample t-test to show differences between levels of BMI and hemoglobin. All statistical analyses were conducted using IBM SPSS version 22.0 software. Results: The results showed a significant difference between hemoglobin levels and different BMI levels (P = 0.03). However, there was no significant relationship between different BMI levels and BUN (P = 0.34), creatinine (P = 0.42), BUN/Cr (P = 0.14), PO2 (P = 0.34), supplementation with oxygen (P = 0.26), and hospitalization rates (P = 0.97). The results according to the normal and abnormal hemoglobin levels were not significant. Conclusion: According to the criteria used in this study to assess nutritional status (BMI and hemoglobin levels), there was no significant relationship between nutritional status (different levels of BMI and hemoglobin) and COVID-19 outcomes, including hospitalization rate, “supplementation with oxygen” rate, and low PO2 levels. Further studies in different countries using other nutritional status assessment tools are needed to confirm these findings.

The Article Abstract is not Available.

Background: Globally 2.73% of pregnant women suffer from hypertension. Currently, there is still a gap of knowledge in Zimbabwe on hypertensive disorders of pregnancy hence the present study. Methods: An analytical cross-sectional study was conducted. The structured checklist was used to extract data. HBP was measured two times on the right arm using an electronic device (OMRON HEM-7261) with an average of two readings. Patient records were used to collect secondary data from prenatal care visits and laboratory tests. We used simple random sampling methods to screen prenatal care records for pregnant women. All pregnant women at Parirenyatwa Group of Hospitals in 2022 were eligible and constituted our study population. The sample size was determined statistically by power analysis using epidemiological information, this yielded a sample of 240. The Prevalence of HBP in pregnancy and risk factors were determined by Fisher exact test Graph Pad (Prism version6.0), P < 0.05 was set as statistically significant. Results: 240 pregnant women were enrolled given a prevalence of HBP of 25%. Most pregnant women having HBP are 36 to 40 years old and located in urban areas (92%, n = 55). Gestational age 33 % (n = 5), Gravida 3-4 (33%, n = 13) Parity 3-4 (74%, n = 25), and Multiple Pregnancy (25%, n = 5) were the most associated with HBP. Pre-existing hypertension was the most common comorbidity 92%.Family history of HBP (OR = 4.62, 95%, CI = 1.4-15.1), p = 0.016) and age being < 30 years OR= 0.26, 95%, CI = 0.14-0.49), p = 0.0001) were associated with HBP. Conclusions: The prevalence of HBP in pregnancy was higher (25%) than the worldwide prevalence of 2.7% and risk factors are mainly age and family history of HBP.

Background: This research aimed to model the structural relationships of attachment styles with for addiction readiness with mediating variable cognitive regulation of emotion in quitting drug addicts. Methods: This is an analytical-cross-sectional study. The sample included 300 rehabilitated addicts (18 to 55 years old) were selected from 4 addiction treatment centers in Amol city in 1401 using stratified random sampling. The tools used in this research were the questionnaire on attachment styles, readiness for addiction,cognitive regulation of emotions. Data analysis was perfprmed based on structural equation modeling in Amos 22 software. Results: The findings manifested that attachment styles affect addiction readiness with the mediating variable being cognitive regulation of emotions in recovering addicts (P = 0.006, P = 0.0001). Attachment styles were directly related to the cognitive regulation of emotions in recovering addicts (P = 0.0001). Cognitive regulation of excitement had a direct association with readiness for addiction in drug addicts who are quitting (P = 0.0001). Conclusion:The results can beapplied in the interventions and trainings of addiction treatment clinics with regard to the predictive power of variables.

Background: Due to the overflow of people in radiation therapy centers and the importance of not interrupting the treatment process, preventive measures is one of the most important measures to deal with COVID-19; therefore, this study aims to evaluate intercultural compatibility, reliability, and validity of COVID-19 prevention measures in a radiation therapy center. Methods: This analytical cross-sectional study was performed with 20 personnel at radiation therapy center of Yazd, Iran using a census method in September 2021. A COVID-19 prevention scale with 29 items was used as measurement tool. First, cultural adaptation was assessed, and then, face validity was determined by calculating the impact score (IS). Content validity was evaluated by calculating the content validity ratio (CVR) and content validity index (CVI), and reliability was determined using the test-retest method, and Kuder–Richardson (KR20) alpha coefficient, and calculating intra-class correlation coefficient (ICC). All the analyses were performed in SPSS software version 24 with a significance level of 5%. Results: 30% (6 people) of the subjects were, 70% (40 people) of whom had less than 15 years of work experience. Four items of the questionnaire were removed based on the minimum Lawshe's CVR values, as their CVR was less than 0.62. Finally, the (KR20) coefficient, scale-level CVI, and ICC were estimated at 0.827, 0.98, and 0.52, respectively. Conclusion: The validity and reliability of the questionnaire were confirmed; therefore, this Persian version of 25-item scale is proposed as a suitable and effective tool for COVID-19 prevention measures in Persian language

The Article Abstract is not available.

Background: Some countries experience lower or higher life expectancy than what is predicted based on their income. This study examines why life expectancy deviation is experienced with the aim of exploring which factors and conditions contribute to better health outcome (life expectancy) at low cost.
 Methods: In this study at the first stage, the well-known Preston curve is reproduced and updated using the cross-sectional data of variables of life expectancy at birth (years) and per capita gross domestic product (GDP) by purchasing power parity (PPP) of 182 countries around the World in 2018 based on the latest available data. After estimating the deviation of each countries life expectancy from the curve, the characteristics of countries with more than four years of positive (group 1) and negative (group 2) gaps from the curve were compared by applying the mean comparison test of two independent groups (t-test).
 Results: The identified drivers of gains or losses in longevity relative to income included using at least basic sanitation (P = 0.012) and drinking water services (P = 0.045), Universal Health Coverage (UHC) (P = 0.012), access to electricity (P = 0.004), CO2 emissions (P = 0.037), inequality in income (P = 0.003), health expenditure per capita (P = 0.000), non-communicable (P = 0.000) and communicable diseases and maternal, prenatal, and nutrition conditions (P = 0.000), literacy rate (P = 0.057), and road injuries (P = 0.001).
 Conclusion: Better health outcome in countries and regions with relatively low income or few resources can be achieved that would be critical for global improvement in population health. However, it needs to take effective measures and is of great importance for policy-making.