Health Promotion Perspectives最新文献

{"title":"Towards attaining universal health coverage in Kazakhstan: Challenges and important next steps.","authors":"Usman Abubakar Haruna, Amos Abimbola Oladunni, Abdulafeez Katibi Abdulkadir, Abbas Bashir Umar, Shuaibu Saidu Musa, Elizabeth Oluwatoyin Afolabi, Joseph Almazan, Don Eliseo Lucero-Prisno Iii","doi":"10.34172/hpp.025.43529","DOIUrl":"10.34172/hpp.025.43529","url":null,"abstract":"<p><p>The Alma Ata Declaration (1978) positioned primary healthcare (PHC) as central to universal health coverage (UHC). Post-independence Kazakhstan struggles with a fragmented healthcare system marked by high mortality, underfunding, and workforce shortages. Despite initiatives like \"Kazakhstan 2050\" and \"Salamatty Kazakhstan,\" challenges persist: economic instability, unregulated private healthcare, high out-of-pocket costs, and rural disparities. While Kazakhstan achieved a 76% UHC index, advancing PHC quality, expanding health financing, and prioritizing rural access remain critical to achieving equitable UHC.</p>","PeriodicalId":46588,"journal":{"name":"Health Promotion Perspectives","volume":"15 1","pages":"3-8"},"PeriodicalIF":2.4,"publicationDate":"2025-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12125506/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144200368","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Association of total, plant, and animal protein intake with hypertension among type 2 diabetic patients in Azar cohort population: A cross-sectional study.","authors":"Sevil Kiani, Sina Naghshi, Elnaz Faramarzi, Maryam Saghafi-Asl","doi":"10.34172/hpp.025.43378","DOIUrl":"10.34172/hpp.025.43378","url":null,"abstract":"<p><strong>Background: </strong>The existing research on the relationship between dietary protein intake and hypertension has mainly centered on the general population, with limited information available for adults with type 2 diabetes (T2DM). Therefore, this study was conducted to explore the association of total, plant, and animal protein intake with hypertension in adults with T2DM.</p><p><strong>Methods: </strong>In this cross-sectional study, 1947 individuals with T2DM from Azar cohort study were included. Dietary data were collected through a validated semi-quantitative food frequency questionnaire (FFQ). Hypertension was defined as blood pressure≥140/90 mm Hg, a self-reported diagnosis of hypertension confirmed by medical records, or the use of anti-hypertensive medications.</p><p><strong>Results: </strong>The mean age of the participants was 54.90 (SD: 8.25) years, with a majority (61%) being female. Initially, a significant positive relationship was observed between total protein intake and the odds of hypertension in the crude model (odds ratio [OR]: 1.38, 95% confidence interval [CI]: 1.04-1.83, <i>P</i>-trend: 0.055). However, after considering potential confounding factors, this association became non-significant (OR: 1.48, 95% CI: 0.94-2.33, <i>P</i>-trend: 0.224). Plant and animal protein intake did not show a significant association with hypertension, neither in the crude model nor in the fully-adjusted model. However, when participants were stratified by gender, a significant association was observed between total protein intake and hypertension only in men (OR: 2.52, 95% CI: 1.13-5.62, <i>P</i>-trend: 0.055).</p><p><strong>Conclusion: </strong>We found no evidence of an association between protein intake and hypertension among individuals with T2DM. However, in stratified analysis, there was a significant positive association between total protein intake and hypertension only in men. Future research should investigate potential, particularly sex-specific, mechanisms that may link dietary protein intake to hypertension in diverse populations.</p>","PeriodicalId":46588,"journal":{"name":"Health Promotion Perspectives","volume":"15 1","pages":"54-62"},"PeriodicalIF":2.4,"publicationDate":"2025-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12125505/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144200359","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Efficacy of digital educational intervention using I-Change model in promoting preventive behaviors for cervical cancer among Iranian women: A randomized controlled trial.","authors":"Sara Kazemi, Fatemeh Zarei, Alireza Hidarnia, Fatemeh Alhani","doi":"10.34172/hpp.025.43722","DOIUrl":"10.34172/hpp.025.43722","url":null,"abstract":"<p><strong>Background: </strong>Cervical cancer (CC) is a major health concern for women, yet stigma and embarrassment often prevent preventive care. Digital health education offers a private, accessible way to learn about CC prevention. This study evaluated the effectiveness of a digital educational intervention based on the I-Change model in promoting preventive behaviors among Iranian women.</p><p><strong>Methods: </strong>A randomized controlled trial (RCT) was conducted with 210 women (18-49 years) from Ramsar, Iran. Participants were assigned to three groups: two intervention groups (mobile app and digital booklet) and a control group. The \"Evaluation of Preventive Behaviors Against CC (PERCICA)\" questionnaire assessed outcomes. The intervention included a pre-test, digital education, and follow-ups immediately and at 12 weeks post-intervention. Data were analyzed using t-tests, analysis of Variance (ANOVA), analysis of covariance (ANCOVA), and repeated measures ANOVA.</p><p><strong>Results: </strong>The app group showed significant improvements in knowledge, perceived risk, self-efficacy, cognitive barriers, and social support (<i>P</i><0.05). Preventive behaviors (e.g., condom use, Pap tests, genital exams) were highest in the app group (67.12%, 95% CI: [29.32±2.35]), followed by the booklet group (38.57%, 95% CI: [9.55±2.17]).</p><p><strong>Conclusion: </strong>The app was more effective in sustaining behavioral changes and promoting CC prevention than the booklet, highlighting the value of tailored digital education for sensitive health topics.</p><p><strong>Trial registration: </strong>ClinicalTrials.gov IRCT20181205041861N3. Registered V2.0 on 26 October 2021 with the IRCTID, V1.0. https://irct.behdasht.gov.ir/trial/57157.</p>","PeriodicalId":46588,"journal":{"name":"Health Promotion Perspectives","volume":"15 1","pages":"44-53"},"PeriodicalIF":2.4,"publicationDate":"2025-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12125502/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144200361","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Step up for wellness: Reducing sedentary lifestyles for a healthier future: Comment on \"Intervening to reduce sedentary behavior among African American elders: the \"Stand Up and Move More\" intervention\".","authors":"Priyanga Chandrasekaran, Priyadharshini Ragavane, Roshni Maria Irwina A","doi":"10.34172/hpp.025.43861","DOIUrl":"10.34172/hpp.025.43861","url":null,"abstract":"","PeriodicalId":46588,"journal":{"name":"Health Promotion Perspectives","volume":"15 1","pages":"1-2"},"PeriodicalIF":2.4,"publicationDate":"2025-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12125504/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144200366","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Serum phospholipids during aging: A comprehensive systematic review of cross-sectional and case-control studies.","authors":"Meysam Zarezadeh, Mahsa Mahmoudinezhad, Amir Hossein Faghfouri, Nima Radkhah, Mehrdad Jamali, Parsa Jamilian, Zohreh Ghoreyshi, Alireza Ostadrahimi","doi":"10.34172/hpp.025.42914","DOIUrl":"10.34172/hpp.025.42914","url":null,"abstract":"<p><strong>Background: </strong>The lipidome, as a subset of metabolomics, can undergo significant variations due to several factors, including the aging process. Therefore, this study aims to summarize the relationship between aging and alterations in plasma phospholipids.</p><p><strong>Methods: </strong>A comprehensive search was conducted in MEDLINE (PubMed), Scopus, Embase, Web of Science, and Google Scholar databases up to September 2023. The PRISMA guidelines were adhered to throughout all stages of the review process. Cross-sectional and case-control studies that investigated the relationship between aging and phosphatidylcholine (PC), lysophosphatidylcholine (LPC), sphingomyelins (SM), ceramides, phosphatidylethanolamines (PE), and phosphatidylinositol (PI) were included.</p><p><strong>Results: </strong>A total of 8486 studies were identified, of which 32 met the predefined inclusion criteria. The systematic review included data from 70,499 participants. The findings revealed that four studies reported a positive association between PCs and aging in both sexes, while one study reported an inverse relationship. Additionally, two studies found that PCs were positively associated with aging in men and negatively associated in women. Furthermore, four studies indicated a negative association between PC metabolites and the aging process. With regard to LPCs, two studies demonstrated a positive correlation, and two studies showed an inverse correlation with aging in both sexes. For SMs, five studies reported a positive association, whereas two studies identified an inverse association with aging trends. Similarly, five studies reported a positive correlation between PE levels and aging, while two studies showed a negative correlation.</p><p><strong>Conclusion: </strong>Phospholipids play a critical role in the aging process, aging-related diseases, and the regulation of lifespan. A reduction in the levels of PCs and LPCs has been identified as a characteristic feature of aging.</p>","PeriodicalId":46588,"journal":{"name":"Health Promotion Perspectives","volume":"15 1","pages":"23-36"},"PeriodicalIF":2.4,"publicationDate":"2025-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12125509/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144200365","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The intersection between pre-existing disability and cancer-survivorship: A narrative review.","authors":"Winston Kennedy, Jafra D Thomas, Gullaiim Almatkyzy, Regina F Hockert","doi":"10.34172/hpp.025.43001","DOIUrl":"10.34172/hpp.025.43001","url":null,"abstract":"<p><strong>Background: </strong>Previous research shows people with pre-existing disabilities face unique societal barriers to health services. The purpose of this review is to promote a better understanding of ways pre-existing disability affects access to cancer-related care through a critical commentary of the research literature.</p><p><strong>Methods: </strong>Systematic search procedures were used to locate articles for inclusion in a narrative review of the research literature. A priori search terms were used to systematically search for eligible articles, using four online databases. These authors thematically analyzed trends in the research findings using a descriptive-interpretive paradigm.</p><p><strong>Results: </strong>Thirteen articles were included in the final narrative review. Four themes were identified: (1) low screening rates, (2) barriers to cancer screening, (3) pre-existing disability moderates cancer incidence, treatment, and survival, and (4) recommendations for supporting improved HRQoL in cancer survivors with pre-existing disability.</p><p><strong>Conclusion: </strong>Our findings illustrate a need for interdisciplinary research focused on ways pre-existing disability intersects with cancer-related healthcare.</p>","PeriodicalId":46588,"journal":{"name":"Health Promotion Perspectives","volume":"15 1","pages":"37-43"},"PeriodicalIF":2.4,"publicationDate":"2025-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12125508/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144200367","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial intelligence survival models for identifying relevant risk factors for incident diabetes in Azar cohort population.","authors":"Neda Gilani, Mohammadhossein Somi, Farzaneh Hamidi, Pasqualina Santaguida, Elnaz Faramarzi, Reza Arabi Belaghi","doi":"10.34172/hpp.025.43105","DOIUrl":"10.34172/hpp.025.43105","url":null,"abstract":"<p><strong>Background: </strong>This study aimed to identify some risk factors associated with time to diabetes type II events using artificial intelligence (AI) survival models (SM) in a population cohort from East Azerbaijan, Iran.</p><p><strong>Methods: </strong>Data from Azar-Cohort spanning from 2014 to 2020 was analyzed using the random forest (RF) variable selection method along with Cox regression to identify the most relevant risk factors associated with diabetes. We then developed prediction models using RF survival analysis. Lasso-variable selection and RF variable selection were used to select the most important variables. The concordance index (C-index) was used to evaluate the concordance of the prediction models.</p><p><strong>Results: </strong>Our LASSO-Cox regression identified six factors to be significantly associated with diabetes: age, mean corpuscular hemoglobin concentration (MCHC), waist circumference (WC), body mass index (BMI), use of sleep medication, and hypertension stage 1 and stage 2. The model included all variables with a C-index of 76.3%. In contrast, the RF analysis identified 21 important variables predicting a higher probability of having diabetes. Of those, WC, MCHC, triglyceride, and age were the most important predictors of diabetes. The RF model converged after 500 trees with an out-of-bag (OOB) of 0.28 and a C-index of 79.5%.</p><p><strong>Conclusion: </strong>RF machine learning algorithms and LASSO-Cox regression analyses consistently identified WC, hypertension, and MCHC as the main risk factors for developing diabetes. The RF approach demonstrated slightly better accuracy in predicting the likelihood of diabetes at different time points.</p>","PeriodicalId":46588,"journal":{"name":"Health Promotion Perspectives","volume":"15 1","pages":"82-92"},"PeriodicalIF":2.4,"publicationDate":"2025-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12125507/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144200418","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Corrigendum to: Medications Non-adherence Reasoning Scale (MedNARS): Development and psychometric properties appraisal.","authors":"Hamid Allahverdipour, Majid Badri, Abdolreza Shaghaghi, Hassan Mahmoodi, Haleh Heizomi, Shayesteh Shirzadi, Mohammad Asghari-Jafarabadi","doi":"10.34172/hpp.025.44568","DOIUrl":"10.34172/hpp.025.44568","url":null,"abstract":"<p><p>[This corrects the article DOI: 10.34172/hpp.2023.26.].</p>","PeriodicalId":46588,"journal":{"name":"Health Promotion Perspectives","volume":"15 1","pages":"93"},"PeriodicalIF":2.4,"publicationDate":"2025-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12125503/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144200360","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine Learning Predictive Models for Survival in Patients with Brain Stroke.","authors":"Solmaz Norouzi, Samira Ahmadi, Shayeste Alinia, Farshid Farzipoor, Azadeh Shahsavari, Ebrahim Hajizadeh, Mohammad Asghari Jafarabadi","doi":"10.34172/hpp.025.43635","DOIUrl":"10.34172/hpp.025.43635","url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusion: </strong>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.</p>","PeriodicalId":46588,"journal":{"name":"Health Promotion Perspectives","volume":"15 1","pages":"63-72"},"PeriodicalIF":2.4,"publicationDate":"2025-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12125501/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144200363","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Psychometric properties of the genderism and transphobia scale in Iranian students.","authors":"Ali Reza Shafiee-Kandjani, Sara Tajlil, Asal Raeisnia, Şenol Turan, Behzad Shalchi","doi":"10.34172/hpp.025.43507","DOIUrl":"10.34172/hpp.025.43507","url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusion: </strong>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.</p>","PeriodicalId":46588,"journal":{"name":"Health Promotion Perspectives","volume":"15 1","pages":"73-81"},"PeriodicalIF":2.4,"publicationDate":"2025-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12125500/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144200364","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}