Journal of Medicine, Surgery, and Public Health最新文献

{"title":"Social factors related to gun violence in urban United States","authors":"Joseph A. McMillan , Sri Banerjee , Rafael Gonzales-Lagos , Wayne Harris","doi":"10.1016/j.glmedi.2024.100155","DOIUrl":"10.1016/j.glmedi.2024.100155","url":null,"abstract":"<div><h3>Introduction</h3><div>Gun violence (GV), acknowledged as a public health crisis, disproportionately affects urban centers in the United States. However, the precise connections between social factors and GV are not fully understood. This study, leveraging the Cardiff Model approach, evaluates whether there is a statistical and geospatial relationship between social vulnerability index (SVI) and GV.</div></div><div><h3>Methods</h3><div>In this cross-sectional study, we combined Gun Violence Archive (GVA), a dataset of firearm violence (2019–2023), with corresponding census tract level SVIs for three selected cities—Atlanta, GA; St. Louis, MO; and Washington, DC. The GVA was created, due to gaps in government-based data, from daily public records and media by an independent data collection group. Also, the SVI, derived from a place-based index from Centers for Disease Control (CDC), was originally used to evaluate the resiliency of communities to recover from socio-environmental stressors. GV data from these three cities, representative of major urban centers in the United States, were used to conduct various analyses. We used Poisson regression to assess whether nine of the sixteen SVI measures were statistically associated with GV incidents. Furthermore, we examined whether spatial relationships between SVI and GV differ by level of concentrated disadvantage in urban neighborhoods.</div></div><div><h3>Results</h3><div>Out of all GV incidents (10,442), corresponding to 488 census tracts, teenagers ages 12–17 were found to have higher GV rates in St. Louis (12 %) than Atlanta (7.6 %) and Washington DC (10.5 %). Children, ages 0–11, in St. Louis (3.1 %) were involved in more GV incidents than the other two (Washington DC-1.2 % and Atlanta-2.3 %) cities. In the composite model, census tract-level SVIs were statistically significantly associated with GV. Some of the most prominent SVIs, viewed as predictors of GV, included racial-ethnic minority [Incidence Rate Ratio (IRR): 1.02, 95 % CI: 1.01–1.02, p<0.001], 150 % of Federal Poverty Level (FPL) [IRR: 1.00, 95 % CI: 1.00–1.01, p<0.001], and unemployment (IRR: 1.01, p<0.001). Also, many of the SVI variables were found to be significantly associated with GV incidents in each of the three selected cities.</div></div><div><h3>Conclusions</h3><div>In this original study, we found that there was a strong statistically significant association between SVI-related disadvantaged neighborhoods and increased GV incidents. Additionally, we found that the geospatial distribution of GV incidents were more concentrated in neighborhoods with increased vulnerability throughout the three (Atlanta, GA; St. Louis, MO; and Washington, DC) selected cities than those neighborhoods with decreased vulnerability. Unique approaches such as integration of the SVI with gun control legislation, which informs ownership, use, and access to firearms, provides a better strategy to inform the implementation of an inter","PeriodicalId":100804,"journal":{"name":"Journal of Medicine, Surgery, and Public Health","volume":"4 ","pages":"Article 100155"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142705099","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":"Sjögren’s syndrome complicated by ischemic stroke in the right middle cerebral artery territory – A case report","authors":"Muhammad Mubashir,&nbsp;Imaan Jauhar,&nbsp;Saba Zaidi","doi":"10.1016/j.glmedi.2024.100104","DOIUrl":"https://doi.org/10.1016/j.glmedi.2024.100104","url":null,"abstract":"<div><p>Sjögren's syndrome (SS) is a chronic autoimmune condition characterized by lymphoplasmacytic infiltration into salivary and lacrimal glands, leading to sicca syndrome and systemic symptoms. While pulmonary, musculoskeletal, dermatological, and renal manifestations are well-documented, reports of central nervous system (CNS) involvement, particularly stroke, remain rare. We present a case report of a 30-year-old female whose initial manifestation of vasculitis associated with Sjögren's syndrome was an ischemic stroke. Laboratory findings revealed a positive ANA profile and radiological investigations showed an infarct in the right middle cerebral artery (MCA). The patient was then managed using steroids, antiplatelets, hydroxychloroquine, and physiotherapy. Although small-vessel vasculitis is commonly implicated in CNS involvement, major cerebral vessel involvement in Sjögren's syndrome is infrequently reported, with only three cases documented in the literature. This case highlights the importance of recognizing stroke as a potential manifestation of Sjögren-related vasculitis and expands the understanding of CNS complications in this autoimmune disorder. Increased awareness of this rare presentation may aid in prompt diagnosis and appropriate management of vasculitic complications in Sjögren's syndrome patients. Further research is needed to elucidate the underlying mechanisms and explore optimal treatment strategies for this subset of patients.</p></div>","PeriodicalId":100804,"journal":{"name":"Journal of Medicine, Surgery, and Public Health","volume":"3 ","pages":"Article 100104"},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949916X24000574/pdfft?md5=49b88ff4a391f053a77f0495aa1e66f8&pid=1-s2.0-S2949916X24000574-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140618833","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":"Lemierre’s syndrome: A clinician's dilemma – A case report","authors":"Usamah Al-Anbagi ,&nbsp;Mohamed I. Abdelrahim ,&nbsp;Mohamad G. Safieh ,&nbsp;Aya M. Abdelgadir ,&nbsp;Rania F. Eisa ,&nbsp;Claret C. Isabirye ,&nbsp;Abdulqadir J. Nashwan","doi":"10.1016/j.glmedi.2024.100116","DOIUrl":"https://doi.org/10.1016/j.glmedi.2024.100116","url":null,"abstract":"<div><p>Lemierre's syndrome (LS) is a life-threatening, rare condition that starts with an oropharyngeal infection leading to internal jugular vein septic thrombophlebitis and potentially severe systemic complications, highlighting the need for prompt recognition and treatment by healthcare professionals. We present a case of LS in a 37-year-old male who initially presented with a sore throat, cough, and high-grade fever. A diagnostic workup revealed a positive blood culture with Fusobacterium necrophorum, and an ultrasound examination demonstrated internal jugular vein thrombophlebitis, confirming the diagnosis of LS. Treatment commenced with oral antibiotics planned for 6 weeks, alongside oral anticoagulation scheduled for 12 weeks. Our case underscores the need for vigilance and multidisciplinary collaboration in managing LS, highlighting the importance of prompt recognition, targeted therapies, and ongoing research to optimize outcomes and enhance diagnosis and management.</p></div>","PeriodicalId":100804,"journal":{"name":"Journal of Medicine, Surgery, and Public Health","volume":"3 ","pages":"Article 100116"},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949916X24000690/pdfft?md5=09209737c536904b80fc4643f51e5c5c&pid=1-s2.0-S2949916X24000690-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141244343","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":"Enhancing mental health with Artificial Intelligence: Current trends and future prospects","authors":"David B. Olawade ,&nbsp;Ojima Z. Wada ,&nbsp;Aderonke Odetayo ,&nbsp;Aanuoluwapo Clement David-Olawade ,&nbsp;Fiyinfoluwa Asaolu ,&nbsp;Judith Eberhardt","doi":"10.1016/j.glmedi.2024.100099","DOIUrl":"https://doi.org/10.1016/j.glmedi.2024.100099","url":null,"abstract":"<div><p>Artificial Intelligence (AI) has emerged as a transformative force in various fields, and its application in mental healthcare is no exception. Hence, this review explores the integration of AI into mental healthcare, elucidating current trends, ethical considerations, and future directions in this dynamic field. This review encompassed recent studies, examples of AI applications, and ethical considerations shaping the field. Additionally, regulatory frameworks and trends in research and development were analyzed. We comprehensively searched four databases (PubMed, IEEE Xplore, PsycINFO, and Google Scholar). The inclusion criteria were papers published in peer-reviewed journals, conference proceedings, or reputable online databases, papers that specifically focus on the application of AI in the field of mental healthcare, and review papers that offer a comprehensive overview, analysis, or integration of existing literature published in the English language. Current trends reveal AI's transformative potential, with applications such as the early detection of mental health disorders, personalized treatment plans, and AI-driven virtual therapists. However, these advancements are accompanied by ethical challenges concerning privacy, bias mitigation, and the preservation of the human element in therapy. Future directions emphasize the need for clear regulatory frameworks, transparent validation of AI models, and continuous research and development efforts. Integrating AI into mental healthcare and mental health therapy represents a promising frontier in healthcare. While AI holds the potential to revolutionize mental healthcare, responsible and ethical implementation is essential. By addressing current challenges and shaping future directions thoughtfully, we may effectively utilize the potential of AI to enhance the accessibility, efficacy, and ethicality of mental healthcare, thereby helping both individuals and communities.</p></div>","PeriodicalId":100804,"journal":{"name":"Journal of Medicine, Surgery, and Public Health","volume":"3 ","pages":"Article 100099"},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949916X24000525/pdfft?md5=0c54ac141de2ae06febf31119e21a63a&pid=1-s2.0-S2949916X24000525-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140633158","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":"Emergence of a more virulent clade of Mpox in Africa: Learning from history and charting a path forward","authors":"Isaac Iyinoluwa Olufadewa,&nbsp;Ruth Ifeoluwa Oladele ,&nbsp;Oluwatayo Ayobami Olajide,&nbsp;Harrison Toluwanimi Adetunji,&nbsp;Godwin Edoseawe Okoduwa,&nbsp;Toluwase Ayobola Olufadewa,&nbsp;Miracle Ayomikun Adesina","doi":"10.1016/j.glmedi.2024.100134","DOIUrl":"10.1016/j.glmedi.2024.100134","url":null,"abstract":"<div><p>The resurgence of Mpox (formerly known as Monkeypox) in Africa, marked by a 160 % increase in cases and a 19 % rise in deaths in 2024 compared to the previous year, is driven by the emergence of a more virulent clade 1b variant. This resurgence, declared a Public Health Emergency of International Concern by the World Health Organization, highlights the persistent challenges in global health equity, particularly in vaccine distribution, public health infrastructure, and surveillance. Drawing from historical lessons, including vaccine inequity during the COVID-19 pandemic and delayed responses in past outbreaks, this paper outlines critical strategies for addressing the current crisis. These strategies include strengthening vaccine equity and access, enhancing community-level surveillance, promoting research and development, implementing comprehensive public health campaigns, and addressing environmental factors that facilitate outbreaks. The paper emphasizes the need for international solidarity and support, proposing the establishment of a global accord to ensure equitable sharing of resources during health emergencies and to prevent low- and middle-income countries from being left behind.</p></div>","PeriodicalId":100804,"journal":{"name":"Journal of Medicine, Surgery, and Public Health","volume":"3 ","pages":"Article 100134"},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949916X24000872/pdfft?md5=e2e72311dc4ea75fbc2e13a74cd18f31&pid=1-s2.0-S2949916X24000872-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142117543","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 for medicine, surgery, and public health","authors":"Jagdish Khubchandani,&nbsp;Srikanta Banerjee,&nbsp;Robert Andrew Yockey,&nbsp;Kavita Batra","doi":"10.1016/j.glmedi.2024.100141","DOIUrl":"10.1016/j.glmedi.2024.100141","url":null,"abstract":"<div><div>Artificial Intelligence (AI) has rapidly transformed many sectors, including medicine, surgery, and public health. While AI has a multitude of unique characteristics that differ from the existing and most commonly used healthcare technologies worldwide, the discussion and publications on AI in healthcare have grown exponentially within the past few years. Despite its transformative potential, AI poses several challenges and there are unanswered questions related to the value and impact of AI on consumers, healthcare providers, and health systems. This editorial explores the growing applications of AI and its potential impacts on key entities in the field of healthcare and public health. Also, through this editorial, the journal editors highlight the urgent need for high-quality and real-world setting-based research on the value of AI in healthcare and public health. Finally, as AI will undoubtedly and significantly continue to impact healthcare consumers and systems, the editors are seeking submissions with rigorous and empirical evidence for AI’s impact on health services consumers and providers, and clinical care facilities or public health organizations. The editors believe that unless scholars worldwide generate robust evidence on the value and impact of AI in healthcare, providing the highest benefits of AI to health services consumers will remain an elusive goal.</div></div>","PeriodicalId":100804,"journal":{"name":"Journal of Medicine, Surgery, and Public Health","volume":"3 ","pages":"Article 100141"},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142420515","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 and big data for pharmacovigilance and patient safety","authors":"Muhammad Aasim Shamim,&nbsp;Muhammad Aaqib Shamim,&nbsp;Pankaj Arora,&nbsp;Pradeep Dwivedi","doi":"10.1016/j.glmedi.2024.100139","DOIUrl":"10.1016/j.glmedi.2024.100139","url":null,"abstract":"&lt;div&gt;&lt;div&gt;Pharmacovigilance, the science of monitoring drug safety, plays a crucial role in identifying and mitigating adverse drug reactions (ADRs). However, underreporting in pharmacovigilance systems—estimated to have a median rate of 94 %—poses a significant threat to patient safety by hindering the detection of safety signals. The need to address these gaps is paramount, especially with the rising complexity of healthcare data. The advent of artificial intelligence (AI) and big data technologies offers promising solutions to overcome the limitations of traditional pharmacovigilance methods.&lt;/div&gt;&lt;div&gt;The application of AI and machine learning (ML) technologies, including natural language processing (NLP) and deep learning, has the potential to revolutionize drug safety monitoring by automating the detection of ADRs from diverse data sources, such as electronic health records (EHRs), spontaneous reporting systems, and social media. These tools can process unstructured data and uncover patterns not easily identifiable through conventional approaches. Additionally, AI can enable real-time pharmacovigilance, which is especially critical in an era of increasing polypharmacy and diverse patient populations. AI-driven models are being utilized to detect drug-drug interactions (DDIs), predict ADRs, and enhance the overall efficiency of pharmacovigilance processes.&lt;/div&gt;&lt;div&gt;Despite these advancements, several challenges remain. The performance of AI models is heavily dependent on the quality and quantity of data available. Inadequate or poorly curated datasets can lead to inaccurate ADR detection, particularly in resource-limited settings. Moreover, the heterogeneity of data sources necessitates robust AI models capable of integrating various types of data while ensuring accurate and reliable outputs. There is also a pressing need to address the transparency and explainability of AI models, as the opaque decision-making processes of current algorithms often impede their acceptance among pharmacovigilance professionals.&lt;/div&gt;&lt;div&gt;Future directions must focus on improving the quality and standardization of datasets, advancing NLP techniques for better interpretation of clinical narratives, and developing explainable AI models. Regulatory frameworks should evolve to support AI deployment in pharmacovigilance, ensuring the establishment of best practices for AI implementation and the creation of large-scale, publicly available training datasets.&lt;/div&gt;&lt;div&gt;Additionally, AI models should go beyond correlation-based approaches by integrating causal inference techniques, which will allow for a more accurate understanding of the relationship between drugs and ADRs. Human oversight will still be required to validate AI findings, but ongoing efforts to improve the robustness of AI systems will reduce dependency on manual interventions and scale the use of AI in pharmacovigilance.&lt;/div&gt;&lt;div&gt;The integration of AI and big data in pharmacovigilance has the potenti","PeriodicalId":100804,"journal":{"name":"Journal of Medicine, Surgery, and Public Health","volume":"3 ","pages":"Article 100139"},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142420514","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":"Loneliness is associated with smoking and alcohol consumption in older adults: Findings from the Chinese Longitudinal Healthy Longevity Survey","authors":"Yusuff Adebayo Adebisi ,&nbsp;Xu Lin ,&nbsp;M.B. N. Kouwenhoven ,&nbsp;Don Eliseo Lucero-Prisno III","doi":"10.1016/j.glmedi.2024.100075","DOIUrl":"https://doi.org/10.1016/j.glmedi.2024.100075","url":null,"abstract":"<div><h3>Introduction</h3><p>Despite the well-known health risks associated with tobacco smoking and alcohol consumption, this study explores the association between loneliness and these behaviors specifically among the elderly in the Chinese context. It examines the relationship between loneliness and the tendency to smoke and drink among this demographic. Additionally, the research investigates how these associations vary between genders among the elderly, identifying distinct patterns in the relationship between loneliness and smoking and alcohol consumption among elderly men and women.</p></div><div><h3>Method</h3><p>This secondary cross-sectional analysis used data from the 2017–2018 Chinese Longitudinal Healthy Longevity Survey. We employed multivariate multinomial logistic regression to analyze these relationships, including sex-specific associations, and reported adjusted odds ratios (AOR), confidence intervals (CI), and p-values. The analysis was conducted using STATA version 18, with significant p-values set at 0.05.</p></div><div><h3>Result</h3><p>Our analysis included 15,874 participants, of which 6.4% (95% CI: 6.0 – 6.8; N=1015) were categorized as Always Lonely, indicating frequent loneliness, and 17.0% (95% CI: 16.4 – 17.6; N=2702) as Sometimes Lonely, indicating occasional loneliness, with 76.6% (95% CI: 75.9 – 77.2; N=12,157) not experiencing loneliness. The mean age was 85.5 years with a standard deviation of 11.7. Gender distribution showed that 43.6% (n=6925) were male and 56.4% (n=8949) were female. Frequently lonely participants had increased odds of current smoking (AOR = 1.26; 95% CI: 1.01–1.57; p = 0.040), while those occasionally lonely were less inclined towards current drinking (AOR = 0.81; 95% CI: 0.70–0.94; p = 0.005). Gender-specific outcomes indicated that often lonely men were more likely to smoke (AOR = 1.43; 95% CI: 1.10–1.87; p = 0.008) and were also less likely to be current drinkers (AOR = 0.74; 95% CI: 0.55–0.98; p = 0.038). No significant associations were found for women in smoking or drinking behaviors relative to loneliness levels.</p></div><div><h3>Conclusion</h3><p>Our study identified a significant relationship between loneliness and a higher likelihood of smoking in elderly Chinese men, not women, and observed gender-specific differences in alcohol use, with men showing a lower likelihood of drinking when occasionally lonely, a pattern absent in women. Future prospective studies are required to confirm these findings.</p></div>","PeriodicalId":100804,"journal":{"name":"Journal of Medicine, Surgery, and Public Health","volume":"3 ","pages":"Article 100075"},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949916X24000288/pdfft?md5=12a1455b3d024e30158a2ce96bdee79a&pid=1-s2.0-S2949916X24000288-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139915120","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 between severe periodontitis and sleep quality: Results from the NHANES, 2009–2014","authors":"Yilin Bao ,&nbsp;Luying Qin ,&nbsp;Mengxuan Hao ,&nbsp;Zhiwei Jiang ,&nbsp;Ying Wang ,&nbsp;Rui Pu","doi":"10.1016/j.glmedi.2024.100114","DOIUrl":"https://doi.org/10.1016/j.glmedi.2024.100114","url":null,"abstract":"<div><p>Periodontitis has a high global prevalence, and sleep may impact both the occurrence and the severity of the condition. With an emphasis on sex disparities, this study examined the association between sleep and severe periodontitis in a population sample that was representative of the United States. This study used a sample of 5495 people from the National Health and Nutrition Examination Survey (NHANES) and conducted univariate and multivariate logistic regression analyses before and after adjusting for age, sex, ethnicity, poverty-income ratio (PIR), body mass index (BMI), smoking status, and diabetes mellitus (DM) status. Furthermore, this study included a stratified sex-based analysis to investigate potential sex differences between severe periodontitis and sleep. The results are presented with odds ratios (ORs) and 95% confidence intervals (95% CIs). The results of multivariate logistic regression revealed a significant association between the recommended sleep duration each night (seven to nine hours) and the prevalence of severe periodontitis in women (OR_ad = 0.68, <em>p</em> = 0.003). Furthermore, in women, urinating twice or three times per night was significantly associated with severe periodontitis (OR_ad = 1.44, <em>p</em> = 0.011), whereas the association was more significant in women who urinated at least four times per night (OR_ad = 1.68, <em>p</em> = 0.035). In men, these associations were not observed. There was no significant association between poor sleep quality and severe periodontitis, but the association differed by sex. Severe periodontitis in women was found to be significantly associated with poor sleep quality, but not in men.</p></div>","PeriodicalId":100804,"journal":{"name":"Journal of Medicine, Surgery, and Public Health","volume":"3 ","pages":"Article 100114"},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949916X24000677/pdfft?md5=577f9ecbe18e26924edae74acb975c79&pid=1-s2.0-S2949916X24000677-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141078635","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":"Pocket money and the risk of dental caries and oral pain in children","authors":"Margaret Trimble ,&nbsp;Sita Manasa Susarla ,&nbsp;Claudia Campos ,&nbsp;Bathsheba Turton ,&nbsp;Karen Sokal-Gutierrez","doi":"10.1016/j.glmedi.2024.100106","DOIUrl":"https://doi.org/10.1016/j.glmedi.2024.100106","url":null,"abstract":"<div><h3>Background</h3><p>Tooth decay affects 40–90 % of children in low- and middle-income countries (LMICs), contributing to adverse consequences, including oral pain, difficulty focusing in school, lifelong dental problems, and overall lower quality of life. Few studies have examined the relationship between pocket money given to children, their purchase of sugary snacks and drinks with that money, and the risk for tooth decay.</p></div><div><h3>Methods</h3><p>This secondary cross-sectional analysis utilized data which were collected in 2014 as part of an oral health promotion program in rural El Salvador. A convenience sample of 279 children and their mothers who participated in the program were recruited to complete an interview with trained community health workers, and children received a dental examination from trained and licensed Salvadoran and U.S. dentists. Only children with teeth (primary, mixed, or permanent dentition) were included in this analysis; as such, children ranged in age from 6 months through 14 years. Descriptive, multivariate logistic regression, and Zero-Inflated Negative Binomial analyses were used to identify associations between pocket money given to children and three oral health outcomes: number of decayed, missing/extracted due to decay, and filled teeth (dmft for primary teeth and DMFT for permanent teeth); presence of deep decay; and occurrence of oral pain.</p></div><div><h3>Results</h3><p>Overall, almost two-thirds of children received daily pocket money with which over 70 % purchased unhealthy snacks/drinks; 83 % of children had tooth decay, with a mean dmft/DMFT of 6.0. After adjusting for covariates, receiving pocket money was associated with 0.18 (95 % CI: 0.05–0.54) times the odds of having zero-dmft/DMFT (i.e., being cavity-free) (<em>p</em> = 0.002). Among children with at least one decayed tooth, receiving pocket money was associated with 1.22 (95 % CI: 1.01–1.53) times the expected dmft/DMFT count (<em>p</em> = 0.04), 3.39 (95 % CI: 1.59–7.22) times the odds of deep decay (<em>p</em> &lt; 0.001), and 2.66 (95 % CI: 1.24–5.70) times the odds of oral pain (<em>p</em> = 0.007) compared to children who did not receive pocket money.</p></div><div><h3>Conclusion</h3><p>Interventions to reduce the prevalence and severity of tooth decay should include nutrition and oral health education for children and families—including addressing pocket money and healthy vs. unhealthy purchases—in schools, communities, and primary health clinics; school programs to provide healthy foods and beverages for children; and enforcement of policies to prohibit the sale of ultra-processed foods and sugary drinks in and around schools.</p></div>","PeriodicalId":100804,"journal":{"name":"Journal of Medicine, Surgery, and Public Health","volume":"3 ","pages":"Article 100106"},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949916X24000598/pdfft?md5=f6e498f69b76d3eae16bd408c2753775&pid=1-s2.0-S2949916X24000598-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140650033","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}