[This corrects the article DOI: 10.34172/hpp.2023.26.].
[This corrects the article DOI: 10.34172/hpp.2023.26.].
Background: This study aims to harness the predictive power of machine learning (ML) algorithms for accurately predicting mortality and survival outcomes in brain stroke (BS) patients.
Methods: A total of 332 patients diagnosed with BS were enrolled in the study between April 21, 2006, and December 22, 2007, and then followed for 15 years (until 2023). Mortality outcomes were modeled using various statistical techniques, including the Cox model, decision trees, random survival forests (RSF), support vector machines (SVM), gradient boosting, and mboost. The best-performing model was selected based on diagnostic performance metrics: specificity, sensitivity, precision, accuracy, area under the receiver operating characteristic curve (AUC), positive likelihood ratio, negative likelihood ratio, and negative predictive value.
Results: The results indicate that ML models in small sample sizes, particularly the SVM, outperformed the Cox model in predicting mortality and survival over 15 years, achieving an accuracy of 85% and an AUC of 0.765 (95% CI 0.637-0.83). Furthermore, the study identified important variables, including blood pressure history, waterpipe smoking, lack of physical activity, type of cerebrovascular accident, current smoking status, sex, and age, which provide valuable insights for clinicians in risk assessment.
Conclusion: Our study showed that the SVM model outperforms the Cox model in predicting 15-year mortality and survival, particularly in small sample sizes. Moreover, the identification of key risk factors such as blood pressure history, waterpipe smoking, lack of physical activity, type of cerebrovascular accident, current smoking status, sex, and age highlights the need for their consideration in clinical assessments to enhance patient care.
Background: Although the prevalence of transgender individuals has increased, there is currently no scale that aligns with Iranian culture to assess transphobia. Therefore, this study aimed to evaluate the validity and reliability of the Persian version of the Genderism and Transphobia Scale (GTS), and its cross-cultural adaptation in an Iranian setting.
Methods: This psychometric study involved 418 students in Tabriz, northwestern Iran. Forward-backward translation was conducted to develop a Persian version of the scale. Reliability was assessed using test-retest, Cronbach's alpha, and the interclass correlation coefficient (ICC) test. Face, content, and construct validity were also evaluated.
Results: The Cronbach's alpha was 0.91 for transphobia/genderism (T/G), 0.83 for gender-bashing (GB) and 0.91 for the total GTS. The results of the exploratory factor analysis (EFA) showed that the two factors, T/G and GB, collectively explained 47.05% of the total variance. The ICCs for different factors of the Persian-GTS including T/G, GB, and GTS total were r=0.79 (Confidence interval [CI] 95%; 0.86 - 0.90), r=0.65 (CI 95%; 0.71 - 0.80), and r=0.98 (CI 95%; 0.68 - 0.79), respectively. An EFA identified two factors defining 47.05% of all the variance. Items number 8 and 31 were removed from the Persian version of GTS.
Conclusion: The Persian-GTS was identified to be valid and reliable for evaluating students' attitudes toward transgender individuals. Consequently, the Persian-GTS can be utilized in research concerning health issues related to transgender individuals.
Background: To evaluate a multi-setting lifestyle intervention's effect on body mass index (BMI) across the entire spectrum in a middle-income adult population over 15 years.
Methods: This pragmatic interventional study included 5153 adults (≥20 years) from a middle-income community, followed for over 15 years with five follow-ups. A multi-setting intervention (school, family, community) aimed to promote healthy lifestyles. The lambda-mu sigma (LMS) method and quantile regression model were used to analyze changes in BMI percentiles (10th-90th) by sex and intervention group.
Results: The intervention showed modest effects on BMI percentiles. In men, it lowered BMI at the 40th and 70th percentiles (overweight/obesity onset) at the first follow-up (β=-0.16, 95% CI: -0.33, -0.001 and β=-0.21, 95% CI: -0.38, -0.04 respectively). In women, the effect emerged later (second follow-up) at the 20th (β=-0.39, 95% CI: -0.60, -0.18), 30th (β=-0.27, 95% CI: -0.49, -0.04), and 60th (β=-0.20, 95% CI: -0.39, -0.02) percentiles (overweight risk), extending to more overweight percentiles (20th-50th) in the third follow-up (βs ranged from -0.28 until -0.26).
Conclusion: Our results indicated the effectiveness of a practical lifestyle intervention to control rising trend of BMI at the onset of overweight and obesity in a middle-income population. These findings can be useful for planning obesity prevention programs in communities with similar socioeconomic statuses.
Background: Global warming is caused by increased carbon dioxide and other industrial gases, which shift the climate of human habitat and environment, impacting human health globally. In this review, we tried to overview the current knowledge of climate change's impact on neurological disease.
Methods: A comprehensive search on PubMed, Web of Science (WOS), and Scopus was conducted to find the relevant original studies. Language, sex, age, date, or country of study were not restricted. Included studies report increased Alzheimer's disease mortality and hospital admission.
Results: This increase was seen from the first day with high temperature to 3-4 days later. Parkinson's disease (PD) subjects were more vulnerable to high temperatures compared to dementia patients (RR for dementia: 1.29 and for PD: 1.41). Global warming was linked to the increase in the incidence of Tick-borne encephalitis (TBE) (from 0.1% to 5.4%), Japanese encephalitis (OR: 2 when floods occur), and ciguatera fish poisoning (CFP) (RR: 1.62 for each 1 ◦C increase per month).
Conclusion: Health-related consequences of climate change are inevitable. The burden of medical problems related to the elderly population (especially the elderly with dementia), infectious diseases, and CFP on the healthcare system will naturally increase. Studying global warming trends could empower us with more precise predictions of the future and better planning to face climate change-related challenges.
Background: Sodium-glucose cotransporter-2 (SGLT-2) acts as a key element in the reabsorption of glucose in the kidney. Currently, SGLT-2 inhibitors are FDA-approved for the treatment of type 2 diabetes. It is suggested that the mechanism of action may operate in the treatment of type 1 diabetes mellitus (T1DM), as well. This study aimed to evaluate the application of empagliflozin as an adjunctive to insulin in patients with T1D.
Methods: In this double-blind placebo-controlled randomized clinical study, 60 type 1 diabetic patients were randomly assigned to have either once-daily empagliflozin 10 mg or placebo, as an addition to insulin for 12 weeks. The hemoglobin A1C, fasting blood sugar (FBS), 2-hour post-prandial blood sugar, and anthropometric indices were measured before and after 12 weeks intervention.
Results: After 12 weeks, empagliflozin resulted in significant reductions of hemoglobin A1C -0.18 (95% CI: -0.37, 0.005, P=0.009), FBS -2.60 mg/dL (95% CI: -6.48, 1.28, P=0.035), 2-hour post-prandial blood sugar -22.56 mg/dL (95% CI: -35.15, 8.97, P<0.0001), and total daily insulin dose -7.6 units (95% CI: -12.4, 2.8, P=0.003). Furthermore, empagliflozin reduced body mass index (BMI) by -0.560 kg (95% CI: -0.640, 1.46, P<0.0001). Empagliflozin was well tolerated in the patients. Also, no case of hypoglycemia, genital and urinary infections, or diabetic ketoacidosis (DKA) was reported.
Conclusion: The present study supported the use of empagliflozin alongside insulin as a treatment option for individuals with T1D.
Trial registration: http://www.irct.ir, identifier: irct20130610013612N12, Registration date: 12/9/2022).
Background: The readiness of health facility services for non-communicable diseases (NCDs) is a critical aspect of global health infrastructure. NCDs, such as cardiovascular diseases, chronic respiratory diseases, and diabetes, pose significant challenges to public health systems worldwide. This study assesses health facility services readiness for NCDs in 8 low- and middle-income countries (LMICs).
Methods: The data is collected using stratified random sampling method with a sample size of 7606 health facilities, the study assesses the health facility services readiness index for general and disease-specific health services by using the survey data from service provision assessment (SPA) between 2015 to 2021 for eight countries under the study. This service readiness index represents the percentage of items considered essential for providing general and specific health services issued by the World Health Organisation.
Results: The mean values of the service readiness index at 95% confidence interval are 56.2%, 37.7%, 35.4%, and 36.5% for the general health services, diabetes, cardiovascular, and respiratory diseases, respectively. These results show substantial variations range from 1% to 20 % in the service readiness index by health facility types in the countries of this study. Overall, public facilities have achieved a higher service readiness index score and, thus, have demonstrated a greater level of preparation in providing general and disease-specific health services for chronic non-communicable diseases.
Conclusion: A substantial number of health facilities in these countries are not adequately prepared to care for chronic NCDs. More investment in critical health infrastructure is urgently needed to strengthen the capacity of health systems in the countries of this study. The investment should focus on achieving universal health coverage (UHC) goals vis-à-vis reducing the burden of premature mortality from chronic diseases.
Background: Children's health is shaped by their physical, natural, and socioeconomic environments. The objective of this study is to identify structural urban planning measures that can positively or negatively impact children's health. Specifically, we aim to explore how urban planning elements, such as housing, neighborhoods, play areas, and green spaces, influence children's well-being and health outcomes.
Methods: We conducted a scoping review in accordance with the method developed by Arksey and O'Malley, Levac and colleagues' methodology advancement, and the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guideline. We explored eight databases, restricting our search to reviews, systematic reviews, and meta-analyses that report on structural measures aimed at modifying urban planning to promote child health.
Results: A total of 41 studies were identified for inclusion in this review. The thematic analysis identified: i) interventions aimed at modifying streets; ii) interventions aimed at modifying play areas; iii) interventions aimed at modifying contact with nature; iv) interventions aimed at modifying deleterious exposures (exposure to tobacco, exposure to school); and v) housing. The second level of analysis enabled us to identify and evaluate the conditions for implementation and effectiveness.
Conclusion: The review highlighted measures that are favorable to children's health at the level of neighborhood urban planning and questioned the conditions for implementation in a French context.
Background: This study aimed to analyze the geographic distribution of diabetes and sedentary behavior across Florida counites, identifying high-risk areas to inform targeted public health interventions. We seek to inform targeted public health interventions and address health disparities, particularly in rural areas.
Methods: Data from the 2017-2019 Florida Behavioral Risk Factor Surveillance System (BRFSS) were analyzed, among adults aged 18 years and older. Diabetes status was determined by self-reported diagnosis, and sedentary behavior was assessed based on physical activity participation. Respondents who declined to answer or were unsure were excluded.
Results: The statewide prevalence of diabetes diagnosis in Florida was 11.7% (95% CI: 10.8-12.6), with substantial geographic variation across counties. Sedentary prevalence varied significantly across the state, compared to the statewide rate of 26.5% (95% CI: 25-28). Counties with high diabetes prevalence often had elevated rates of sedentary behavior. Rural northern panhandle counties had higher concentrations of both diabetes and sedentary behavior. BRFSS design variables and weights ensured representative estimates for Florida.
Conclusion: This study highlights the elevated prevalence of diabetes and sedentary lifestyles in the northern counties of Florida. The geographic patterns underscore the need for targeted, county-level interventions. Despite troubling rise in diabetes and sedentary behavior, there is a significant opportunity to mobilized community and outreach services, ensuring they are effectively deployed to these high-risk areas.
Background: Achieving sleep consolidation, during the first years of life can be a key factor affecting child growth and development. To our knowledge, for the first time, we aimed to systematically assess the relationships between sleep consolidation and growth and development in early childhood.
Methods: Following the latest version of PRISMA, PubMed, Web of Science, and Scopus were searched up to February 2023. We included observational studies in which 0-3-year-old children were enrolled and the association between sleep consolidation and either children's growth or development were assessed. The quality assessment was done using the NIH quality assessment tool.
Results: Out of the 342 studies initially screened, 18 studies met the eligibility criteria, encompassing a total of 10068 infants and toddlers under 3 years of age. Overall, not in all but in some studies sleep consolidation showed a significant association with better cognitive, social-emotional and language outcomes. However, the relationship between sleep consolidation and motor development was less clear, with no significant associations observed across the studies. Additionally, no significant connections were found between sleep consolidation and physical growth indices, such as body mass index (BMI) or weight gain.
Conclusion: According to the existing evidence, at least, the potential associations between sleep consolidation and child development particularly cognitive, social-emotional, and language cannot be ruled out. However, due to the heterogenicity of results and inconsistent findings in some studies, we cannot still strongly declare that sleep consolidation is a remarkable predictor for child growth and development.
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