Journal of Global Health最新文献

{"title":"Editor's view: What makes science successful?","authors":"Igor Rudan","doi":"10.7189/jogh.15.01005","DOIUrl":"10.7189/jogh.15.01005","url":null,"abstract":"<p><p>This editorial examines the factors contributing to the success of science, tracing its evolution from fundamental human curiosity to contemporary advancements propelled by technology, data, and artificial intelligence (AI). Beginning with the hypothesis-testing process, it highlights how imaginative individuals throughout history have offered explanations for the natural world, designed experiments, and amassed evidence to confirm or reject their ideas and theories, thus generating new knowledge and understanding of nature. Early humans formulated simple myths and legends as the first scientific hypotheses, partly to lessen their fear of the unknown. A more scientific turn appeared when rare explorer-scientists ventured beyond their ancestral homes, gathered empirical information using their limited senses, made choices based on observations, and sometimes relocated entire communities. Their efforts reflected the timeless elements of the scientific method: from generating a hypothesis to its experimental proof, broad validation and application of new knowledge. The paper then examines the characteristics of successful scientific disciplines. They attract many researchers who generate novel ideas and hypotheses, building an accelerating momentum of discovery. Further hallmarks of such fields are swift and fair peer validation and robust mechanisms for applying new knowledge to improve human well-being. By contrast, less successful fields will struggle with attracting talent, leading to slower progress, which could also be coupled with resistance to new ideas and obstacles to real-world translation of new knowledge. A central theme of the paper is the contribution of measurement and tools to science's success. Modern instruments, from microscopes and telescopes to satellites and statistical tools, have extended our perception of nature, revealing realms far smaller and far larger than human senses can access. The paper also addresses the revolution of 'hypothesis-free science', driven by computers and big data. Rather than framing a single hypothesis, modern researchers gather enormous datasets and use algorithms to test large numbers of possible hypotheses simultaneously and systematically, free of human bias introduced through existing knowledge. Finally, the paper explores how AI could advance science to unprecedented successes: not just by improving human senses like a microscope does, providing additional ones like the Large Hadron Collider does, or extending human memory and computational capacity like computers do, but also by expanding human reasoning itself. Unlike previous tools, AI can synthesise human knowledge and generate hypotheses, design studies, explore patterns and write papers, thus becoming both a 'philosopher 2.0' and a 'scientist 2.0'. Therefore, AI may transform science from a human-centred endeavour into collaborative effort that relies on hybrid intelligence. This unprecedented new frontier will require attention to","PeriodicalId":48734,"journal":{"name":"Journal of Global Health","volume":"15 ","pages":"01005"},"PeriodicalIF":4.5,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12278886/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144676243","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prevalence of malnutrition and associated factors in Chinese children and adolescents aged 3-14 years using machine learning algorithms.","authors":"Fangjieyi Zheng, Kening Chen, Xiaoqian Zhang, Qiong Wang, Zhixin Zhang, Wenquan Niu","doi":"10.7189/jogh.15.04204","DOIUrl":"10.7189/jogh.15.04204","url":null,"abstract":"<p><strong>Background: </strong>Child malnutrition represents a critical global public health issue and it is characterised by high prevalence and severe long-term consequences for growth and development. A better understanding of its contributory factors is essential to inform the design of targeted prevention strategies and evidence-based interventions. We aimed to estimate the prevalence of malnutrition in children and adolescents aged 3-14 years, and further to identify promising factors associated with child malnutrition using machine learning algorithms.</p><p><strong>Methods: </strong>Thirty kindergartens and 26 schools were randomly selected from Beijing and Tangshan. Child malnutrition was defined according to WHO standards. Factors for child malnutrition were selected by Logistic regression and three ensemble learning algorithms. An open-access web platform was developed to facilitate calculating probabilities of child malnutrition.</p><p><strong>Results: </strong>Total 18 503 children and adolescents were surveyed, and 10.93% (n = 2022) of them were found to be malnourished. Random forest emerged as the best model, as it carried the highest area under the receiver operating characteristic curve (AUROC) at 0.929. Under the implementation of random forest, top eight factors that formed the optimal set for child malnutrition prediction were identified, including age, frequency of fast food intake, frequency of late-night snacking, family history of diabetes, duration of breastfeeding, sedentary time, and parental body mass index. Further Logistic regression analyses confirmed the predictive significance of these individual factors.</p><p><strong>Conclusions: </strong>We have identified eight contributory factors for malnutrition in 3-14-year-old children and adolescents in Beijing and Tangshan, with their prediction performance optimal under random forest. More studies among independent populations are warranted to validate our findings.</p>","PeriodicalId":48734,"journal":{"name":"Journal of Global Health","volume":"15 ","pages":"04204"},"PeriodicalIF":4.5,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12278689/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144676245","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Construction workers' depression, anxiety, stress, and risk factors in China: a cross-sectional study.","authors":"Zhicheng Ling, Yuying Xu, Minmin Tao, Binbin Zhang, Meng Zhang, Zhiding Zhang, Xiaoya DA, Xinmin Liu, Long Huang","doi":"10.7189/jogh.15.04167","DOIUrl":"10.7189/jogh.15.04167","url":null,"abstract":"<p><strong>Background: </strong>Frontline construction workers are generally faced with risk factors such as alcoholism, smoking, and being far away from home, which pose a great threat to their mental health. However, this issue has not yet attracted significant attention form the global community. For this reason, we examined depression, anxiety, and stress levels among construction workers in China and identified their key risk factors, such as education, occupational tenure, geographical mobility, physical well-being, COVID-19 status, insomnia, and alcohol dependency.</p><p><strong>Methods: </strong>We conducted an online survey using validated scales, including the Depression, Anxiety, and Stress Scale, Insomnia Severity Index Scale, Alcohol Dependence Scale, Family-work Conflict Scale, Leadership Support Scale, Workplace Exclusion Scale, and Proactive Personality Scale.</p><p><strong>Results: </strong>We analysed 912 valid responses (790 males, 122 females; mean age = 36.35 years (standard deviation = 10.11). Depression, anxiety, and stress levels were significantly influenced by age, education, work-related injuries, COVID-19 status, insomnia, alcohol dependence, workplace exclusion, and work-family conflict among construction workers (all P-values < 0.05). The regression analysis showed that work-family conflict, workplace exclusion, alcohol dependence, and insomnia were positively associated with depression (P < 0.001), while proactive personality and leadership support were negatively associated with depression (all P-values <0.05). Similarly, physical health, workplace exclusion, alcohol dependence, and insomnia were positively associated with anxiety (all P-values <0.001). Additionally, having a proactive personality negatively influenced depression (P < 0.001). Anxiety positively predicted physical health issues (P < 0.001), workplace exclusion (P < 0.001), alcohol dependence (P < 0.001), and insomnia (P < 0.001), whereas leadership support reduced anxiety levels (P = 0.01).</p><p><strong>Conclusions: </strong>Mental health risks among construction workers are linked to work and personal factors, including insomnia, alcohol dependence, workplace exclusion, and work-family conflict. Employers should implement targeted interventions to improve the work environment, leadership support, and social support systems to enhance the workers' mental well-being.</p>","PeriodicalId":48734,"journal":{"name":"Journal of Global Health","volume":"15 ","pages":"04167"},"PeriodicalIF":4.5,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12278889/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144676241","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial intelligence platform to predict children's hospital care for respiratory disease using clinical, pollution, and climatic factors.","authors":"William Cabral-Miranda, Cauê Beloni, Felipe Lora, Rogério Afonso, Thales Araújo, Fátima Fernandes","doi":"10.7189/jogh.15.04207","DOIUrl":"10.7189/jogh.15.04207","url":null,"abstract":"<p><strong>Background: </strong>Hospitals and health care systems may benefit from artificial intelligence (AI) and big data to analyse clinical information combined with external sources. Machine learning, a subset of AI, uses algorithms trained on data to generate predictive models. Air pollution is a known risk factor for various health outcomes, with children being a particularly vulnerable group.</p><p><strong>Methods: </strong>This study developed and validated an AI-based platform to forecast paediatric emergency visits and hospital admissions for respiratory diseases, using clinical and environmental data in the Metropolitan Area of São Paulo, Brazil. We applied XGBoost, a tree-based machine learning algorithm, to predict hospital use at Sabará Children's Hospital, incorporating clinical, pollution, and climatic variables.</p><p><strong>Results: </strong>We analysed 24 366 emergency department visits and 2973 hospital admissions for respiratory diseases International Classification of Diseases, 10th Revision, Chapter J (ICD-10 J), excluding COVID-19, from January to December 2022. Only geocoded cases within the spatial accuracy thresholds of the study were included. Logistic regression revealed that outpatient visits were associated with higher particulate matter with a diameter of 10 µm or less (PM₁₀) concentrations near children's residences on the day of hospital arrival. In contrast, admissions were linked to lower relative humidity, particularly on drier days. Additional associations were found between admissions and the spring season, as well as male sex.</p><p><strong>Conclusions: </strong>We developed a platform that integrates clinical and environmental databases within a big data framework to process and analyse information using AI techniques. This tool predicts daily emergency department and hospital admission flows related to paediatric respiratory diseases. The algorithms can distinguish whether a child arriving at the emergency department is likely to be treated and discharged or will require hospital admission. This predictive capability may support hospital planning and resource allocation, particularly in contexts of environmental vulnerability.</p>","PeriodicalId":48734,"journal":{"name":"Journal of Global Health","volume":"15 ","pages":"04207"},"PeriodicalIF":4.5,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12278686/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144676240","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring healthcare facilities' readiness for standard precautions in infection prevention and control: a cross-country comparative analysis of six low- and middle-income countries using national cross-sectional surveys.","authors":"Md Abdullah Al Jubayer Biswas, Scott J Adams, Li Xing, Prosanta Mondal, Michael Szafron","doi":"10.7189/jogh.15.04205","DOIUrl":"10.7189/jogh.15.04205","url":null,"abstract":"<p><strong>Background: </strong>Despite the significant morbidity and mortality caused by healthcare-associated infections worldwide, especially in low- and middle-income countries (LMICs), there is a lack of understanding of the readiness to apply standard precautions for infection prevention and control (IPC) in healthcare facilities across different LMICs.</p><p><strong>Methods: </strong>We analysed nationally representative health system data from the Service Provision Assessment surveys for six selected LMICs - Afghanistan, the Democratic Republic of Congo, Haiti, Nepal, Senegal, and Bangladesh. We recorded seven tracer items of standard precautions into binary elements. We calculated a readiness index based on the World Health Organization's Service Availability and Readiness Assessment manual. We utilised survey-weighted multivariable generalised estimating equations to identify factors associated with the readiness index.</p><p><strong>Results: </strong>Among 6054 healthcare facilities, 55% (95% confidence interval (CI) = 53.1, 56.5) of necessary standard precautions were available, ranging from 48.1% in the Democratic Republic of the Congo to 65% in Nepal. Readiness varied by service area, with the tuberculosis service area being the least prepared at 38% and the general outpatient service area being the most prepared at 66%. Facilities in Nepal and the urban regions showed higher readiness, with mean (x̄) differences of 16% (95% CI = 13.6, 17.9) and 3% (95% CI = 1.8, 4.9) compared to the Democratic Republic of the Congo and rural areas, respectively.</p><p><strong>Conclusions: </strong>We revealed significant deficiencies in standard precautions within healthcare facilities across six LMICs, notably in rural areas. The findings underscore an urgent need for targeted interventions to improve IPC strategies, particularly in domains like tuberculosis care.</p>","PeriodicalId":48734,"journal":{"name":"Journal of Global Health","volume":"15 ","pages":"04205"},"PeriodicalIF":4.5,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12278887/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144676244","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Determining the cause of death through mortality surveillance using verbal autopsy in Karachi, Pakistan.","authors":"Raheel Allana, Inci Yildirim, Shabina Ariff, Sameer M Belgaumi, Nazia Ahsan, Obianuju Aguolu, Sabeen Umair, Sehrish Amir Ali, Tehreem Maqsood, Mohammad Iqbal, Fauzia Aman Malik, Saad B Omer, Abdul Momin Kazi","doi":"10.7189/jogh.15.04199","DOIUrl":"10.7189/jogh.15.04199","url":null,"abstract":"<p><strong>Background: </strong>In Pakistan, cultural and religious beliefs restrict autopsies, limiting their prevalence. Additionally, many deaths occur at home, outside of hospital systems, making cause-of-death (CoD) determination challenging. This study aims to overcome these challenges by using a community-based verbal autopsy approach in Karachi to identify CoD.</p><p><strong>Methods: </strong>The research was conducted in two peri-urban communities within the Health Demographic Site Surveillance catchment area. A total of 1500 deaths were investigated using the World Health Organization 2016 Verbal Autopsy Questionnaire. Interviewers received extensive training to ensure culturally sensitive data collection, and physicians analysed the data to determine CoD. The 10th edition of the International Classification of Diseases (ICD-10) was integrated with verbal autopsy data for a detailed analysis of mortality causes.</p><p><strong>Results: </strong>The study identified that 52.8% of deaths were male, and 47.1% female, with 51.2% occurring in hospitals and 48.7% at home. Among home deaths, 31.5% were children under five years and 55.4% were above 18 years. Analysis revealed that major CoD included non-communicable diseases: acute cardiac disease (12.6%), liver cirrhosis (7%), and stroke (4.3%), alongside communicable diseases like diarrheal disease (6.4%), pneumonia (4.1%), and sepsis (3.4%). In adults over 18, acute cardiac disease (25.0%) and liver cirrhosis (13.1%) were prevalent, whereas neonatal sepsis (12.8%) and perinatal asphyxia (11.7%) were the most common causes in children under five years. External causes included road traffic crashes (1.6%) and accidental drowning (0.7%).</p><p><strong>Conclusions: </strong>The study underscores the need for targeted health care strategies to address the diverse CoD and varying health-seeking behaviours observed. Improving access to health care, particularly for home-based deaths and vulnerable age groups, is essential for better health outcomes. Tailored interventions are crucial to address both communicable and non-communicable diseases effectively in resource-constrained settings.</p>","PeriodicalId":48734,"journal":{"name":"Journal of Global Health","volume":"15 ","pages":"04199"},"PeriodicalIF":4.5,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12278687/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144676242","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatiotemporal evolution and impacts of environment on scrub typhus in northern China, 2006-2019.","authors":"Ting Li, Xianjun Wang, Yamei Wang, Chenxin Gu, Liping Yang","doi":"10.7189/jogh.15.04202","DOIUrl":"10.7189/jogh.15.04202","url":null,"abstract":"<p><strong>Background: </strong>Scrub typhus is a significant public health issue with a global distribution. In northern China, Shandong Province is a major endemic area, but its spatiotemporal patterns and influencing factors remain unclear.</p><p><strong>Methods: </strong>This study collected data on scrub typhus in Shandong Province from the Infectious Disease Reporting System of the Shandong Center for Disease Control and Prevention between 2006 and 2019. Spatiotemporal evolution analysis combined joinpoint regression, spatiotemporal cluster analysis and standard deviation ellipse. GeoDetector was used to identify the impacts of socioeconomic and natural factors on spatial distribution of scrub typhus. Generalised additive model was applied to explore associations with meteorological variables.</p><p><strong>Results: </strong>9397 scrub typhus cases were reported in Shandong Province from 2006 to 2019, with an average annual incidence of 0.68 / 100 000, peaking in 2014 (1.53 / 100 000). Cases were concentrated from September to November. Spatiotemporal cluster was mainly in Linyi and Rizhao cities in southern Shandong. The centre of gravity of scrub typhus gradually shifted southeast, and moved back from 2015 to 2019. Nighttime light (q = 0.223), normalised difference vegetation index (q = 0.197), relief degree of land surface (q = 0.230), grassland (q = 0.320), and water (q = 0.180) were all related with scrub typhus, with q indicating the explanatory power of each factor on the spatial distribution of the disease. The strongest relative risks between monthly incidence of scrub typhus and temperature, humidity, precipitation and humidex were 1.528 (lag3), 1.175 (lag3), 1.013 (lag1), and 1.279 (lag3), respectively.</p><p><strong>Conclusions: </strong>Scrub typhus in Shandong Province was mainly concentrated in Linyi and Rizhao cities. The occurrence of scrub typhus is influenced by various environmental factors. Humidex is a better composite indicator to reflect the impacts of meteorological factors on scrub typhus in northern China. These findings provide scientific evidence to guide prevention and control strategies for scrub typhus. Limitations include potential underreporting in surveillance data and the absence of vector and host information.</p>","PeriodicalId":48734,"journal":{"name":"Journal of Global Health","volume":"15 ","pages":"04202"},"PeriodicalIF":4.5,"publicationDate":"2025-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12278688/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144676246","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring the complex relationship between systemic lupus erythematosus and coronavirus disease 2019: genetic insights and potential protective mechanisms.","authors":"Xiaoli Xu, An-Tian Chen, Yantao Ding, Tingting Zhu, Luyao Xia, Jingkai Xu, Liyue Sun, Lu Liu","doi":"10.7189/jogh.15.04191","DOIUrl":"10.7189/jogh.15.04191","url":null,"abstract":"<p><strong>Background: </strong>Severe coronavirus disease 2019 (COVID-19) and systemic lupus erythematosus (SLE) have been reported to share common gene loci, but the causal relationship between them remains controversial.</p><p><strong>Methods: </strong>We conducted a linkage disequilibrium score regression analysis to assess the genetic correlations between SLE and the two traits (infection and severity) of COVID-19 in European populations. Mendelian randomisation analysis was then performed to explore the causal effect of SLE on susceptibility to these traits in both European and East Asian data sets. Lastly, enrichment analysis and Protein-Protein Interactions analysis were used to identify key pathways and genes involved, providing insights into the possible mechanism underlying the complex relationship between SLE and COVID-19.</p><p><strong>Results: </strong>A significant genetic correlation was observed between SLE and COVID-19 severity (genetic correlation (rg) = 0.340, P = 0.001). However, no significant genetic correlation was found with COVID-19 infection. Mendelian randomisation analysis revealed a negative causal effect of SLE on both COVID-19 infection (odds ratio (OR) = 0.986; 95% confidence interval (CI) = 0.975-0.997, P = 0.009) and severity (OR = 0.955; 95% CI = 0.921-0.990, P = 0.012) in European populations, with similar findings replicated in East Asians. Notably, interleukin-6 (IL-6) and tumour necrosis factor were identified as hub cytokines connecting SLE to COVID-19 infection, while IL-6 and interleukin-10 (IL-10) were pivotal in connecting SLE to COVID-19 severity.</p><p><strong>Conclusions: </strong>This study reveals a potentially protective effect of SLE against COVID-19 infection and severity, with IL-6, tumour necrosis factor, and IL-10 playing key roles. Despite immunosuppressant use, SLE patients showed no increased risk of severe outcomes, likely due to their heightened caution in avoiding infection. These findings challenge common assumptions and highlight the need for further research.</p>","PeriodicalId":48734,"journal":{"name":"Journal of Global Health","volume":"15 ","pages":"04191"},"PeriodicalIF":4.5,"publicationDate":"2025-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12247663/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144610058","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Outcomes of children aged 2-59 months with chest indrawing pneumonia managed on an outpatient basis in selected primary health facilities in Zambia.","authors":"Choolwe Jacobs, Chipo Nkwemu, Bryan Bakele Ngambi, Vichael Silavwe, Shamim Ahmad Qazi, Yasir Bin Nisar","doi":"10.7189/jogh.15.04089","DOIUrl":"10.7189/jogh.15.04089","url":null,"abstract":"<p><strong>Background: </strong>Zambia has a high burden of child pneumonia, with approximately 6000 children under five dying annually from this condition. We aimed to gather evidence about the outcomes two weeks after enrolment for children 2-59 months with chest indrawing pneumonia who were managed in primary health care facilities in Zambia.</p><p><strong>Methods: </strong>This was a prospective cohort study conducted between October 2022 and April 2024 in eight primary health care facilities from Lusaka, Chibombo, and Chongwe districts. Children aged 2-59 months with cough and/or breathing difficulty and lower chest indrawing were enrolled, treated on an outpatient basis according to the Integrated Management of Childhood Illness (IMCI) protocol, and followed up on day 15 after enrolment.</p><p><strong>Results: </strong>We enrolled 335 children in the study (median age of 17 months, 56.4% female). Among them, 63% were aged 12-59 months, 23.6% had a height-for-age z-score of<-3.0, and 10.5% had a weight-for-age z-score of<-3.0. By day 15, 314 children had follow-up data, all of whom survived. Of these, 77.1% were cured, 22.9% were reported as being 'clinically better', and none failed therapy. Most children were treated with oral amoxicillin (84.1%), with a cure rate of 82.2%. Children treated with cotrimoxazole (60% cure rate) and erythromycin (26.7% cure rate) had lower success rates. A higher proportion of girls (81.4%) were cured compared to boys (71.5%), and children who were fully vaccinated (79.6%) had a higher cure rate than those who were partially or not vaccinated (48.0%). Children of educated parents had higher cure rates than those of uneducated parents.</p><p><strong>Conclusions: </strong>Children with chest indrawing pneumonia were successfully treated with oral amoxicillin in an outpatient setting, improving access to treatment and reducing costs for both health care systems and families. This approach also helps reduce the risk of healthcare-associated infections. It is essential that health care providers in primary health facilities are trained to use IMCI protocols when managing children under five.</p>","PeriodicalId":48734,"journal":{"name":"Journal of Global Health","volume":"15 ","pages":"04089"},"PeriodicalIF":4.5,"publicationDate":"2025-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12247661/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144610060","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Setting stakeholder-led research priorities for advancing Sexual and Reproductive Health and Rights in Bangladesh using CHNRI method: an icddr,b initiative.","authors":"Abu Sayeed, Nondo Saha, Shafiqul Ameen, Ema Akter, Lubna Hossain, Md Mehedi Hasan, Fariya Rahman, Sahar Raza, Saraban Tahura Ether, Sabit Saad Shafiq, Hassan Rushekh Mahmood, Ashfia Saberin, Sabina Ashrafee, Husam Md Shah Alam, Palash Kumar Saha, Sabbir Haider, Supriya Sarkar, Mustufa Mahmud, Md Jahurul Islam, Shumona Sharmin Salam, Quamrun Nahar, Shams El Arifeen, Anisuddin Ahmed, Ahmed Ehsanur Rahman","doi":"10.7189/jogh.15.04186","DOIUrl":"10.7189/jogh.15.04186","url":null,"abstract":"<p><strong>Background: </strong>Sexual and reproductive health and rights (SRHR) are essential for individuals' health, well-being, survival, and economic development. A stakeholder-led approach to research prioritisation was essential to guide SRHR-related research in Bangladesh. Accordingly, we conducted a research prioritisation exercise to identify health research priorities related to SRHR in Bangladesh.</p><p><strong>Methods: </strong>We adopted the Child Health and Nutrition Research Initiative (CHNRI) method for this study. Five themes - adolescent Health (AH), fertility, gynaecological issues (GI), maternal and neonatal health (MNH), and SRH of key populations (SRHKP) - were selected from the broader field of SRHR. Seventy-six experts submitted 454 research questions (RQs), which were then condensed into 197 unique RQs and distributed to all experts for scoring based on five pre-selected criteria. Weighted and unweighted research priority scores (RPS) and average expert agreement (AEA) were calculated to compile a list of top-ranked RQs.</p><p><strong>Results: </strong>The weighted RPSs for the 197 RQs ranged from 0.944 to 0.623, with a median of 0.848. Among the top 20 list, six RQs belonged to AH, one to Fertility, two to GI, six to MNH, and five to SRHKP. For AH, top ranked RQs included adolescent pregnancy, sexual health education, and mental health. Promoting proper birth spacing among newlywed and underaged married women were top RQs for fertility. GI priorities emphasised early detection of gynaecological cancers, including HPV testing for cervical cancer screening. The MNH research focused on Newborn Stabilizing Units at sub-district hospitals, PPH bundle approaches, and counselling on danger signs to prevent adverse birth outcomes. The top-ranked RQs in SRHKP addressed stigma and discrimination towards key populations (KPs) and their impact on SRH behaviours. There was significant overlap between the top 20 RQs ranked by RPS and AEA.</p><p><strong>Conclusions: </strong>The study emphasises the need for intervention research to address barriers, assess effectiveness, and enhance the uptake of evidence-based and innovative interventions for SRHR in Bangladesh.</p>","PeriodicalId":48734,"journal":{"name":"Journal of Global Health","volume":"15 ","pages":"04186"},"PeriodicalIF":4.5,"publicationDate":"2025-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12247414/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144610062","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}