How far has the globe gone in achieving One Health?Current evidence and policy implications based on global One Health index

Background:In the 21st century,as globalization accelerates and global public health crises occur,the One Health approach,guided by the holistic thinking of human-animal-environment and emphasizing interdisciplinary collaboration to address global health issues,has been strongly advocated by the international community.An immediate requirement exists for the creation of an assessment tool to foster One Health initiatives on both global and national scales.Methods:Built upon extensive expert consultations and dialogues,this follow-up study enhances the 2022 global One Health index(GOHI)indicator system.The GOHI framework is enriched by covering three indices,e.g.external drivers index(EDI),intrinsic drivers index(IDI),and core drivers index(CDI).The comprehensive indicator system incorporates 13 key indicators,50 indicators,and 170 sub I-indicators,utilizing a fuzzy analytic hierarchy process to ascertain the weight for each indicator.Weighted and summed,the EDI,IDI,and CDI scores contribute to the computation of the overall GOHI 2022 score.By comparing the ranking and the overall scores among the seven regions and across 160 countries/territories,we have not only derived an overall profile of the GOHI 2022 scores,but also assessed the GOHI framework.We also compared rankings of indicators and sub Iindicators to provide greater clarity on the strengths and weaknesses of each region within the One Health domains.Results:The GOHI 2022 performance reveals significant disparities between countries/territories ranged from 39.03 to 70.61.The global average score of the GOHI 2022 is 54.82.The average score for EDI,IDI,and CDI are 46.57,58.01,and 57.25,respectively.In terms of global rankings,countries from North America,Europe and Central Asia,East Asia and Pacific present higher scores.In terms of One Health domains of CDI,the lowest scores are observed in antimicrobial resistance(median:43.09),followed by food security(median:53.78),governance(median:54.77),climate change(median:64.12)and zoonotic diseases(median:69.23).Globally,the scores of GOHI vary spatially,with the highest score in North America while lowest in sub-Saharan Africa.In addition,evidence shows associations between the socio-demographic profile of countries/territories and their GOHI performance in certain One Health scenarios.Conclusion:The objective of GOHI is to guide impactful strategies for enhancing capacity building in One Health.With advanced technology and an annually updated database,intensifying efforts to refine GOHI's data-mining methodologies become imperative.The goal is to offer profound insights into disparities and progressions in practical One Health implementation,particularly in anticipation of future pandemics.

Diagnostic value comparison of the combination of prostate-specific membrane antigen-body PET/MR and the prostate health index with each alone in early diagnosis of prostate cancer

Objective:This study aimed to figure out whether the combination of the prostate health index(PHI)and prostate-specific membrane antigen(PSMA)-PET/MR could improve the diagnostic accuracy for prostate cancer(PCa)than that of each individual method used alone.Methods:In this prospective,observational study,41 patients who underwent the systematic prostate biopsy between June 2019 and September 2022 were enrolled.Both the PHI test and ^(18)F-PSMA-1007-PET/MR were performed prior to biopsies.The diagnostic accuracy of different models was compared by logistic regression,areas under the curve(AUCs)of the receiver operating characteristic,and net reclassification index(NRI).Results:Among the 41 patients,14(34.1%)were pathologically diagnosed with PCa.The PHI in the PCa group was significantly higher than that in the benign group(44.4 vs.35.0,p=0.048).Similarly,all the patients in the PCa group received positive results of ^(18)F-PSMA-1007-PET/MR,of which the positive rate was significantly higher than that in benign group(100%vs.62.96%,p=0.025).The ^(18)F-PSMA-1007-PET/MR provided additional diagnostic values to the PHI(AUC:0.802 vs.0.692,p=0.025).However,there was no significant difference between the combination model and the ^(18)F-PSMA-1007-PET/MR alone(AUC 0.802 vs.0.685,p=0.071).The optimal PHI cutoff of the combination model is 32,with which the model could significantly reduce unnecessary biopsies(NRI:22.22%,95%confidence interval:6.54%–37.90%,p=0.005).However,among patients with the PHI of≥43.5,there was no significant difference between the combination model and the PHI alone(NRI:11.11%,95%confidence interval:−0.74%–22.97%,p=0.066).Conclusion:The combination of the PHI and ^(18)F-PSMA-1007-PET/MR outperforms the PHI alone for predicting PCa,especially in avoiding unnecessary biopsies.However,for patients with the PHI of≥43.5,the addition of ^(18)F-PSMA-1007-PET/MR to the PHI does not yield additional benefits.

Effects of serum inflammatory factors,health index and disease activity scores on ankylosing spondylitis patients with sleep disorder

BACKGROUND Patients with ankylosing spondylitis(AS)frequently suffer from comorbid sleep disorders,exacerbating the burden of the disease and affecting their quality of life.AIM To investigate the clinical significance of serum inflammatory factors,health index and disease activity scores in patients with AS complicated by sleep disorders.METHODS A total of 106 AS patients with comorbid sleep disorders were included in the study.The patients were grouped into the desirable and undesirable prognosis groups in accordance with their clinical outcomes.The serum levels of inflammatory factors,including C-reactive protein,erythrocyte sedimentation rate,interleukin(IL)-6,tumour necrosis factor-αand IL-1β,were measured.Disease activity scores,such as the Bath AS functional index,Bath AS disease activity index,Bath AS metrology index and AS disease activity score,were assessed.The health index was obtained through the Short Form-36 questionnaire.RESULTS The study found significant associations amongst serum inflammatory factors,health index and disease activity scores in AS patients with comorbid sleep disorders.Positive correlations were found between serum inflammatory factors and disease activity scores,indicating the influence of heightened systemic inflammation on disease severity and functional impairment.Conversely,negative correlations were found between disease activity scores and health index parameters,highlighting the effect of disease activity on various aspects of healthrelated quality of life.Logistic regression analysis further confirmed the predictive value of these factors on patient outcomes,underscoring their potential utility in risk assessment and prognostication.CONCLUSION The findings demonstrate the intricate interplay amongst disease activity,systemic inflammation and patientreported health outcomes in AS patients complicated by sleep disorders.The results emphasise the need for comprehensive care strategies that address the diverse needs and challenges faced by these patients and underscore the potential relevance of serum inflammatory factors,health index and disease activity scores as prognostic markers in this patient population.

A Bibliometric Analysis of Positive Mental Health Research and Development in the Social Science Citation Index

Background:This study aimed to conduct a bibliometric analysis of positive mental health,focusing on citation performance,article title,abstract,author keywords,Keyword Plus,and their development trends.The novelty of this study is a pioneer within the field of positive mental health.Therefore,it delivered new ideas for researchers and practitioners who had concerns about positive mental health in terms of trends research which covered recommended articles and the research focus in recent years.Methods:The data were retrieved on 30 April 2024 from the Social Sciences Citation Index(SSCI)of Clarivate Analytics’Web of Science Core Collection for studies published between 1992 and 2023.Results:The distribution of keywords in the article title and keywords chosen by the authors were used to assess research trends.1391 documents in SSCI were found during the search;1221 of these were document-type“articles.”524 journals published these publications.The most frequently used keywords by the writers,according to the articles’analysis,are“depression,”“resilience,”“COVID-19,”“anxiety,”and“social support.”Kristin D.Neff wrote the most frequently cited paper in 2003.Most articles came from Europe(five countries),America(two countries),Asia(two countries),and Oceania(one country),and were published in English.The majority of the research in the field of positive mental health is conducted in Europe and America,two regions where English is the primary language.The main research topics in positive mental health were related to adolescents,children,and college students.Conclusion:Trends research through bibliometric analysis by using data from Web of Science Core Collection should be followed by manual inspection to avoid errors.Therefore,scientists need more careful data examination in bibliometric analysis.

Metaverse for mental health disorders:Opportunities and challenges

Several articles on the mental health impact of the metaverse and the need to balance its potential benefits with the risks of metaverse use has recently published.The metaverse consists of a combination of immersive technologies and artificial intelligence algorithms.The metaverse differs from the preceding digital psychiatric interventions due to its complex structure and interactions between components.The diverse functions of the metaverse ensure that it may have a substantial impact on mental health.However,the evidence for its efficacy in treating mental health disorders is limited to a few trials.The mental health benefits of immersive technologies are well-documented and suggest that metaverse-based psychiatric treatment may be similarly efficacious.The mental health risks of the metaverse are largely unknown,and it is not clear whether they will be greater than other digital psychiatric interventions.Much more research is needed to determine whether metaverse-based psychiatric treatment will meet the standards of appropriate mental healthcare.

Ultra‑High Sensitivity Anisotropic Piezoelectric Sensors for Structural Health Monitoring and Robotic Perception

Monitoring minuscule mechanical signals,both in magnitude and direction,is imperative in many application scenarios,e.g.,structural health monitoring and robotic sensing systems.However,the piezoelectric sensor struggles to satisfy the requirements for directional recognition due to the limited piezoelectric coefficient matrix,and achieving sensitivity for detecting micrometer-scale deformations is also challenging.Herein,we develop a vector sensor composed of lead zirconate titanate-electronic grade glass fiber composite filaments with oriented arrangement,capable of detecting minute anisotropic deformations.The as-prepared vector sensor can identify the deformation directions even when subjected to an unprecedented nominal strain of 0.06%,thereby enabling its utility in accurately discerning the 5μm-height wrinkles in thin films and in monitoring human pulse waves.The ultra-high sensitivity is attributed to the formation of porous ferroelectret and the efficient load transfer efficiency of continuous lead zirconate titanate phase.Additionally,when integrated with machine learning techniques,the sensor’s capability to recognize multi-signals enables it to differentiate between 10 types of fine textures with 100%accuracy.The structural design in piezoelectric devices enables a more comprehensive perception of mechanical stimuli,offering a novel perspective for enhancing recognition accuracy.

Low‑Temperature Fabrication of Stable Black‑Phase CsPbI_(3) Perovskite Flexible Photodetectors Toward Wearable Health Monitoring

Flexible wearable optoelectronic devices fabricated fromorganic–inorganic hybrid perovskites significantly accelerate the developmentof portable energy,biomedicine,and sensing fields,but their poor thermal stabilityhinders further applications.Conversely,all-inorganic perovskites possessexcellent thermal stability,but black-phase all-inorganic perovskite filmusually requires high-temperature annealing steps,which increases energy consumptionand is not conducive to the fabrication of flexible wearable devices.In this work,an unprecedented low-temperature fabrication of stable blackphaseCsPbI3perovskite films is demonstrated by the in situ hydrolysis reactionof diphenylphosphinic chloride additive.The released diphenyl phosphateand chloride ions during the hydrolysis reaction significantly lower the phasetransition temperature and effectively passivate the defects in the perovskitefilms,yielding high-performance photodetectors with a responsivity of 42.1 AW−1 and a detectivity of 1.3×10^(14)Jones.Furthermore,high-fidelity imageand photoplethysmography sensors are demonstrated based on the fabricated flexible wearable photodetectors.This work provides a newperspective for the low-temperature fabrication of large-area all-inorganic perovskite flexible optoelectronic devices.

Mediating role of health literacy in the relationship between social isolation and psychological distress among pre-frail older adults

BACKGROUND Frailty has become a significant public health issue.The recent increase in the number of frail older adults has led to increased attention being paid to psycho-logical care services in communities.The social isolation of pre-frail older adults can impact their psychological distress.AIM To explore the mediating effect of health literacy between social isolation and psychological distress among communitydwelling older adults with pre-frailty.METHODS This descriptive cross-sectional study was conducted with 254 pre-frail older individuals aged 60 years and over.Social isolation,health literacy,and psycholo-gical distress were comprehensively measured using the Lubben Social Network Scale-6,12-item Short-Form Health Literacy Questionnaire,and the Kessler Psy-chological Distress Scale-10.Data were evaluated using the SPSS 27.0 package program and the PROCESS macro tool.Descriptive statistical analyses,correlation analyses,and bootstrap mediation tests were used to assess associations between the variables.RESULTS The results showed that social isolation had an effect on health literacy among pre-frail older adults(β=0.240,P<0.001),social isolation impact on psycho-logical distress pre-frail older adults(β=-0.415,P<0.001);health literacy was identified effect on psychological distress among pre-frail older persons(β=-0.307,P<0.001).Health literacy partially mediated the relationship between social isolation and psychological distress among community-dwelling older adults with pre-frailty,with a mediation effect of-0.074,accounting for 17.83%of the total effect.

Decoding the nexus:branched-chain amino acids and their connection with sleep,circadian rhythms,and cardiometabolic health

The sleep-wake cycle stands as an integrative process essential for sustaining optimal brain function and,either directly or indirectly,overall body health,encompassing metabolic and cardiovascular well-being.Given the heightened metabolic activity of the brain,there exists a considerable demand for nutrients in comparison to other organs.Among these,the branched-chain amino acids,comprising leucine,isoleucine,and valine,display distinctive significance,from their contribution to protein structure to their involvement in overall metabolism,especially in cerebral processes.Among the first amino acids that are released into circulation post-food intake,branched-chain amino acids assume a pivotal role in the regulation of protein synthesis,modulating insulin secretion and the amino acid sensing pathway of target of rapamycin.Branched-chain amino acids are key players in influencing the brain's uptake of monoamine precursors,competing for a shared transporter.Beyond their involvement in protein synthesis,these amino acids contribute to the metabolic cycles ofγ-aminobutyric acid and glutamate,as well as energy metabolism.Notably,they impact GABAergic neurons and the excitation/inhibition balance.The rhythmicity of branchedchain amino acids in plasma concentrations,observed over a 24-hour cycle and conserved in rodent models,is under circadian clock control.The mechanisms underlying those rhythms and the physiological consequences of their disruption are not fully understood.Disturbed sleep,obesity,diabetes,and cardiovascular diseases can elevate branched-chain amino acid concentrations or modify their oscillatory dynamics.The mechanisms driving these effects are currently the focal point of ongoing research efforts,since normalizing branched-chain amino acid levels has the ability to alleviate the severity of these pathologies.In this context,the Drosophila model,though underutilized,holds promise in shedding new light on these mechanisms.Initial findings indicate its potential to introduce novel concepts,particularly in elucidating the intricate connections between the circadian clock,sleep/wake,and metabolism.Consequently,the use and transport of branched-chain amino acids emerge as critical components and orchestrators in the web of interactions across multiple organs throughout the sleep/wake cycle.They could represent one of the so far elusive mechanisms connecting sleep patterns to metabolic and cardiovascular health,paving the way for potential therapeutic interventions.

A Comprehensive Survey on Federated Learning Applications in Computational Mental Healthcare

Mental health is a significant issue worldwide,and the utilization of technology to assist mental health has seen a growing trend.This aims to alleviate the workload on healthcare professionals and aid individuals.Numerous applications have been developed to support the challenges in intelligent healthcare systems.However,because mental health data is sensitive,privacy concerns have emerged.Federated learning has gotten some attention.This research reviews the studies on federated learning and mental health related to solving the issue of intelligent healthcare systems.It explores various dimensions of federated learning in mental health,such as datasets(their types and sources),applications categorized based on mental health symptoms,federated mental health frameworks,federated machine learning,federated deep learning,and the benefits of federated learning in mental health applications.This research conducts surveys to evaluate the current state of mental health applications,mainly focusing on the role of Federated Learning(FL)and related privacy and data security concerns.The survey provides valuable insights into how these applications are emerging and evolving,specifically emphasizing FL’s impact.

Relationship between the use of smart medical services and mental health status

In this editorial,I comment on the article by Zhang et al.To emphasize the importance of the topic,I discuss the relationship between the use of smart medical devices and mental health.Smart medical services have the potential to positively influence mental health by providing monitoring,insights,and inter-ventions.However,they also come with challenges that need to be addressed.Understanding the primary purpose for which individuals use these smart tech-nologies is essential to tailoring them to specific mental health needs and prefe-rences.

Health anxiety and work loss in patients diagnosed with serrated polyposis syndrome:A cross sectional study

BACKGROUND Serrated polyposis syndrome(SPS)is a polyposis condition with neoplastic potential,but its psychological impact is not well understood.AIM To assess health anxiety prevalence in a regional Australian cohort of SPS patients and explore factors influencing it,including workforce impacts of regular surveillance.METHODS This cross-sectional study screened patients aged 18-65 undergoing colonoscopy in a regional gastroenterology practice between January 2015 and June 2022.Eligible SPS patients were invited to participate.Data included the Short Health Anxiety Inventory,employment status,and previous demographic and medical findings.RESULTS Health anxiety was found in 21.57%of SPS patients,with anxious patients being significantly more concerned about surveillance(OR=7.70).Patients lost an average of 11.04 work hours per colonoscopy.CONCLUSION Health anxiety in SPS patients aligns with rates in other gastroenterology populations.Identifying it may improve management,though further research is needed to better understand prevalence and care improvements.

Method for Estimating the State of Health of Lithium-ion Batteries Based on Differential Thermal Voltammetry and Sparrow Search Algorithm-Elman Neural Network

Precisely estimating the state of health(SOH)of lithium-ion batteries is essential for battery management systems(BMS),as it plays a key role in ensuring the safe and reliable operation of battery systems.However,current SOH estimation methods often overlook the valuable temperature information that can effectively characterize battery aging during capacity degradation.Additionally,the Elman neural network,which is commonly employed for SOH estimation,exhibits several drawbacks,including slow training speed,a tendency to become trapped in local minima,and the initialization of weights and thresholds using pseudo-random numbers,leading to unstable model performance.To address these issues,this study addresses the challenge of precise and effective SOH detection by proposing a method for estimating the SOH of lithium-ion batteries based on differential thermal voltammetry(DTV)and an SSA-Elman neural network.Firstly,two health features(HFs)considering temperature factors and battery voltage are extracted fromthe differential thermal voltammetry curves and incremental capacity curves.Next,the Sparrow Search Algorithm(SSA)is employed to optimize the initial weights and thresholds of the Elman neural network,forming the SSA-Elman neural network model.To validate the performance,various neural networks,including the proposed SSA-Elman network,are tested using the Oxford battery aging dataset.The experimental results demonstrate that the method developed in this study achieves superior accuracy and robustness,with a mean absolute error(MAE)of less than 0.9%and a rootmean square error(RMSE)below 1.4%.

Assessing healthcare workers’knowledge and confidence in the diagnosis,management and prevention of Monkeypox

BACKGROUND Monkeypox(Mpox),is a disease of global public health concern,as it does not affect only countries in western and central Africa.AIM To assess Burundi healthcare workers(HCWs)s’level of knowledge and confidence in the diagnosis and management of Mpox.METHODS We conducted a cross-sectional study via an online survey designed mainly from the World Health Organization course distributed among Burundi HCWs from June-July 2023.The questionnaire comprises 8 socioprofessional-related questions,22 questions about Mpox disease knowledge,and 3 questions to assess confidence in Mpox diagnosis and management.The data were analyzed via SPSS software version 25.0.A P value<0.05 was considered to indicate statistical significance.RESULTS The study sample comprised 471 HCWs who were mainly medical doctors(63.9%)and nurses(30.1%).None of the 22 questions concerning Mpox knowledge had at least 50%correct responses.A very low number of HCWs(17.4%)knew that Mpox has a vaccine.The confidence level to diagnose(21.20%),treat(18.00%)or prevent(23.30%)Mpox was low among HCWs.The confidence level in the diagnosis of Mpox was associated with the HCWs’age(P value=0.009),sex(P value<0.001),work experience(P value=0.002),and residence(P value<0.001).The confidence level to treat Mpox was significantly associated with the HCWs’age(P value=0.050),sex(P value<0.001),education(P value=0.033)and occupation(P value=0.005).The confidence level to prevent Mpox was associated with the HCWs’education(P value<0.001),work experience(P value=0.002),residence(P value<0.001)and type of work institution(P value=0.003).CONCLUSION This study revealed that HCWs have the lowest level of knowledge regarding Mpox and a lack of confidence in the ability to diagnose,treat or prevent it.There is an urgent need to organize continuing medical education programs on Mpox epidemiology and preparedness for Burundi HCWs.We encourage future researchers to assess potential hesitancy toward Mpox vaccination and its associated factors.

Posttraumatic stress symptoms among Chinese university students during the COVID-19 pandemic:Prevalence,correlates,and mental health help-seeking

BACKGROUND Revisiting the epidemiology of posttraumatic stress symptoms(PTSSs)among university students during the coronavirus disease 2019(COVID-19)pandemic as well as understanding the mental health help-seeking behavior of individuals with PTSSs has critical implications for public mental health strategies in future medical pandemics.AIM To investigate the prevalence and correlates of PTSSs among university students during the first wave of the COVID-19 pandemic in China and to examine mental health help-seeking behaviors among these students.METHODS A total of 2507 Chinese university students were recruited via snowball sampling.The students completed the Seven-item Screening Scale for Post-traumatic Stress Disorder during the first wave of the COVID-19 pandemic in China.Sociodemo-graphic characteristics,pandemic-related characteristics,and mental health help-seeking behaviors of students with PTSSs were also collected.RESULTS The prevalence of PTSSs among the participants was 28.0%.Seven significant correlates of PTSSs were identified(odds ratio=1.23-3.65,P≤0.024):Female sex,being 19 years old or older,living with others or alone,a low level of family economic status,fair or poor interpersonal relationships,severe or very severe local pandemic,and having family members diagnosed with COVID-19.However,only 3.28%of the students with PTSSs reported seeking help from mental health specialists.Among the 23 students who sought help from mental health specialists,13 opted for online or telephone-based psychological consultation.CONCLUSION Our data suggest that there was a high risk of PTSSs among university students and a high level of unmet mental health needs during the COVID-19 pandemic.The delivery of mental health services online or via telephone is a promising approach to address these unmet needs.

Cross-sectional study of the association between triglyceride glucose-body mass index and obstructive sleep apnea risk

BACKGROUND The triglyceride glucose-body mass index(TyG-BMI)is a novel indicator of insulin resistance(IR).Obstructive sleep apnea(OSA)is a prevalent disorder characterized by recurrent complete or partial collapse of the pharyngeal airway during sleep;however,the relationship between these two conditions remains unexplored.We hypothesized that a higher TyG-BMI is associated with the occurrence of OSA.AIM To assess the association between TyG-BMI and OSA in adults in the United States.METHODS A cross-sectional study was conducted utilizing data from the National Health and Nutrition Examination Surveys spanning from 2005-2008 to 2015-2018.TyGBMI was calculated as Ln[triglyceride(mg/dL)×fasting blood glucose(mg/dL)/2]×BMI.Restricted cubic splines were used to analyze the risk of TyG-BMI and OSA occurrence.To identify potential nonlinear relationships,we combined Cox proportional hazard regression with smooth curve fitting.We also conducted sensitivity and subgroup analyses to verify the robustness of our findings.RESULTS We included 16794 participants in the final analysis.Multivariate regression analysis showed that participants with a higher TyG-BMI had a higher OSA incidence.After adjusting for all covariates,TyG-BMI was positively correlated with the prevalence of OSA(odds ratio:1.28;95%confidence interval:1.17,1.40;P<0.001);no significant nonlinear relationship was observed.Subgroup analysis showed no strong correlation between TyG-BMI and OSA in patients with diabetes.The correlation between TyG-BMI and OSA was influenced by age,sex,smoking status,marital status,hypertensive stratification,and obesity;these subgroups played a moderating role between TyGBMI and OSA.Even after adjusting for all covariates,there was a positive association between TYG-BMI and OSA prevalence.CONCLUSION A higher TyG-BMI index is linked to higher chances of developing OSA.As TyG-BMI is an indicator of IR,managing IR may help reduce the risk of OSA.

Impact of community public health care on treatment effect,health cognition,and self-management in patients with type 2 diabetes

BACKGROUND At present,China has become the country with the largest number of individuals with diabetes mellitus(DM)in the world,with a total of approximately 140 million patients,the majority of whom have type 2 DM(T2DM).Based on conven-tional nursing methods,community home care has important clinical significance in controlling blood sugar and disease progression.AIM To explore the impact of community public health nursing on treatment effect,health cognition,and self-management in patients with T2DM.METHODS One hundred patients with T2DM were selected as the research subjects.The patients were divided into either a conventional nursing group or community nursing(CN)group using the random number table method.The conventional nursing group(50 cases)received routine care,while the CN group(50 cases)received community public health care in addition to routine care as that for the conventional nursing group.The rate of excellent and good blood glucose control,fasting blood glucose before and after care,2-h postprandial blood glucose,health cognition,and self-management ability,and patient satisfaction were compared between the two groups.RESULTS The CN group had a higher rate of excellent blood sugar control than the conventional nursing group(88%vs 70%,P<0.05).Before care,there was no significant difference in fasting blood glucose or 2-h postprandial blood glucose between the two groups of patients(P>0.05).After nursing,fasting blood glucose and 2-h postprandial blood glucose were reduced to varying degrees in both groups,and both blood glucose levels in the CN group were lower than those of the conventional nursing group(P<0.05).Compared with the scores before care,the cognitive level score for diabetes and self-management ability score improved after care in both groups.The cognitive level and self-management ability of patients in the CN group were higher than those of the conventional nursing group(P<0.05).The overall satisfaction of the CN group was better than that of the conventional nursing group(98%vs 86%,P<0.05).CONCLUSION Community public health care based on conventional care of T2DM can achieve better blood sugar control,and improve patients’health cognitive level and self-management ability.

A cross-sectional study of the association between dietary inflammatory index and glaucoma prevalence in a US population

AIM:To assess the relationship between dietary inflammatory index(DII)and prevalence of glaucoma among individuals aged 40y and above in the United States.METHODS:Participants were drawn from 2 cycles of the National Health and Nutrition Examination Survey(NHANES,2005-2008)for a cross-sectional study.DII was calculated from 24-hour dietary recall questionnaire conducted by experienced researchers and data analyzed in R according to the NHANES user guide,“Stratified Multi-stage Probability Sampling”.The relationship between DII and glaucoma was evaluated by multi-factor logistic regression analysis and the existence of a non-linear association examined by restricted cubic spline(RCS)analysis.RESULTS:A total of 5359 subjects were included and the cross-sectional analysis weighted to represent the US population of 109 million.DII was elevated in glaucoma patients(P<0.001)and smoking and alcohol use contributed to significant differences(P<0.001).DII correlated negatively with Healthy Eating Index(HEI)-2015(Spearman rank correlation coefficient,r=-0.49).RCS analysis showed a linear relationship between DII and glaucoma risk(P of non-linear relationship=0.575).CONCLUSION:An increased DII is strongly associated with high risk of glaucoma and diet-induced inflammation should be controlled to delay glaucoma progression.

Predicting Standardized Precipitation Evapotranspiration Index for Fada N’Gourma by 2050 Using CMPI-6 Outputs under SSPs Scenarios

Extreme weather events,such as floods and droughts,are expected to rise significantly worldwide as a result of climate change.Investigating future drought patterns is therefore a key approach for elaborating anticipatory water resources management responses to climate change.In this paper,future meteorological drought conditions are investigated based on the SPEI(Standardised Precipitation Evapotranspiration Index).This study makes use of observed and projected data.The simulated data were retrieved from the CMIP6(Coupled Model Intercomparison Project Phase 6)over the period 2025-2050,and the Delta change method was adopted to remove the bias in the dataset.Then SPEI at various scales has been estimated under four future scenarios(SSP1-2.6,SSP2-4.5,SSP3-7.0 and SSP5-8.5).The trend analysis of the projected SPEI was performed at p<0.05 using the MMK(Modified Mann-Kendall)test in order to detect the statistically significant trend of the drought against the null hypothesis of no trend.Results show large variability in the magnitude of drought in the past and future.Based on SPEI at 24 months accumulation,the result shows that under SSP1-2.6,the basin will experience a wet period during the first decade(SPEI=0.60),the second decade will be dry(SPEI24=-0.43).The remaining years will be also dry(SPEI=-0.34).Under SSP2-4.5,SSP3-7.0 and SSP5-8.5 scenarios,the district will experience a wet period during the first two decades with SPEI ranging from 0.38 to 0.59.This wet period will be followed by a dry period under these scenarios ranging from-0.14 to-0.06.Overall,under SSPs scenarios,two main periods characterized by a rainfall recovery spanning from followed by a moderately prolonged drought are identified within the study area.The findings of this study may provide valuable information for developing proactive measures to reduce water insecurity in Fada N’Gourma through effective drought mitigation.

Reevaluating health metrics:Unraveling the limitations of disabilityadjusted life years as an indicator in disease burden assessment

In 1993,the World Bank released a global report on the efficacy of health promotion,introducing the disability-adjusted life years(DALY)as a novel indicator.The DALY,a composite metric incorporating temporal and qualitative data,is grounded in preferences regarding disability status.This review delineates the algorithm used to calculate the value of the proposed DALY synthetic indicator and elucidates key methodological challenges associated with its application.In contrast to the quality-adjusted life years approach,derived from multi-attribute utility theory,the DALY stands as an independent synthetic indicator that adopts the assumptions of the Time Trade Off utility technique to define Disability Weights.Claiming to rely on no mathematical or economic theory,DALY users appear to have exempted themselves from verifying whether this indicator meets the classical properties required of all indicators,notably content validity,reliability,specificity,and sensitivity.The DALY concept emerged primarily to facilitate comparisons of the health impacts of various diseases globally within the framework of the Global Burden of Disease initiative,leading to numerous publications in international literature.Despite widespread adoption,the DALY synthetic indicator has prompted significant methodological concerns since its inception,manifesting in inconsistent and non-reproducible results.Given the substantial diffusion of the DALY indicator and its critical role in health impact assessments,a reassessment is warranted.This reconsideration is imperative for enhancing the robustness and reliability of public health decisionmaking processes.