The Waist-adjusted Weight Index (WWI) is a novel anthropometric marker, its association with dyslipidemia in Asian populations remains unclear. This study examines the relationship between WWI and dyslipidemia in Japanese adults. Grounded in adipose tissue dysfunction and metabolic syndrome mechanisms, WWI, an index of central adiposity independent of body weight, serves as a biologically plausible predictor of dyslipidemia. We retrospectively analyzed 15,453 adults, undergoing health examination from Gifu Murakami Memorial Hospital (1994-2016). Logistic regression and fitted smooth curve analysis assessed WWI and dyslipidemia associations. Stratified analyses were performed based on sex, age, exercise, alcohol consumption, and smoking. WWI was positively associated with dyslipidemia (Adjusted OR = 1.30, 95% CI: 1.21-1.39). Risk increased across quartiles: Q2 (OR = 1.20), Q3 (OR = 1.36), Q4 (OR = 1.44). Smooth curve analysis indicated a nonlinear, accelerating increase. Associations were stronger in men, adults >60, smokers, drinkers, and those with insufficient exercise (P < 0.05). The findings support mechanistic links proposed by the adipose tissue disease theory and metabolic syndrome model, highlighting WWI as a simple, effective early screening tool for dyslipidemia. Prospective studies are needed to validate its predictive value in clinical and public health practice.

OBJECTIVES:With the intensification of aging, the proportion of people affected by multimorbidity is steadily increasing worldwide. In remote areas of China, where economic development is lagging and healthcare resources are limited, the older hypertensive population may experience a higher burden of multimorbidity. However, comprehensive evidence is still lacking on how specific combinations of lifestyle behaviours (LBs) impact particular multimorbidity health outcomes in older hypertensive individuals. STUDY DESIGN:A cross-sectional study was conducted among the older hypertensive population (aged ≥65 years) from 1 July to August 31, 2023 in Jia County, a remote area of China. METHODS:A total of 40 diseases were categorized into physical, psychological and cognitive disorders. Multivariable-adjusted logistic regression models were used to estimate ORs and 95 % CIs for the associations between LBs and multimorbidity. RESULTS:Among 17,728 participants, the prevalence of physical, psychological, cognitive, physical-psychological multimorbidity (PPsM), physical-cognitive multimorbidity (PCM), psychological-cognitive multimorbidity (PsCM), and physical-psychological-cognitive multimorbidity (PPsCM) were 63.55 %, 30.12 %, 64.55 %, 22.31 %, 42.03 %, 22.57 %, and 16.74 %, respectively. Compared to participants without any healthy LBs, those with five healthy LBs were associated with a lower risk of physical, psychological, cognitive, PPsM, PCM, PsCM, and PPsCM. Overall, the risk of adverse outcomes decreased with the number of healthy LBs (Ptrend<0.001). However, combinations of healthy LBs of the same quantity but from different categories exhibited varying impacts on the outcomes. CONCLUSIONS:Multimorbidity involving physical, psychological, and cognitive disorders poses a significant challenge for managing hypertention. Strengthening the capacity of primary healthcare workers to promote healthy lifestyle practices and identifying the optimal LB combinations should be prioritized in the management of hypertensive individuals in remote areas of China.

Sleep is a fundamental biological process that regulates immunity and metabolism and sustains healthy mood. This study aims to identify distinct sleep pattern phenotypes among older adults with chronic diseases in China and investigate their associations with physical and mental health. We conducted a nationally representative survey of 6,559 Chinese patients aged ≥ 60 years with chronic diseases. Using finite normal mixture modeling, we identified sleep patterns from sleep duration, sleep quality, supplementary sleep, and sleep rhythm. Frailty, depression, anxiety, loneliness, and self-rated health were measured using validated scales. Multiple linear regression and subgroup analysis were performed to explore the associations between sleep patterns and health outcomes. Four sleep pattern phenotypes were identified, namely the relatively balanced (3627, 55.3

OBJECTIVE:This study examined the association between allostatic load and trouble sleeping and assessed whether this relationship varies based on allostatic load score (ALS) criteria. METHODS:This cross-sectional survey utilized nationally representative data from the National Health and Nutrition Examination Survey (NHANES). ALS was derived using empirical and clinical criteria based on eight biomarkers reflecting cardiovascular, metabolic, and immune function. Weighted multivariate logistic regression was employed to analyze the association between ALS and trouble sleeping, with subgroup analyses conducted to assess gender-specific differences. RESULTS:Of 5331 participants included in this study, 1485 (29 %) reported trouble sleeping. In multivariate-adjusted logistic regression, higher ALS was associated with increased odds of trouble sleeping (empirical ALS: OR 1.13 [95 % CI 1.07-1.18]; clinical ALS: OR 1.08 [95 % CI 1.04-1.13]). Subgroup analyses confirmed the consistency of this association across genders. CONCLUSION:This study provides robust evidence of a significant association between ALS and trouble sleeping, supported by observed OR of 1.13 (empirical) and 1.08 (clinical). The consistency of findings across both empirical and clinical ALS underscores the potential role of physiological dysregulation in sleep health, highlighting the need for integrated approaches to stress and sleep management.

ObjectiveThe objective of this study was to examine the relationship between sleep duration and prediabetes, as well as to evaluate the influence of inflammation in mediating this association.MethodsA total of 4632 participants from the China Health and Retirement Longitudinal Study (CHARLS) were included in this study, comprising both baseline and 4-year follow-up data. The prospective relationship between sleep duration and the risk of prediabetes was examined using logistic regression models. We used multinomial logistic regression to evaluate the impact of prediabetes on sleep duration changes over follow-up, assessing the role of C-reactive protein in the association using mediation analysis.ResultsParticipants with short sleep duration (<5 hours) had a higher risk of prediabetes (odds ratios=1.381 [95% CI: 1.028-1.857]) compared to those with normal sleep durations (7-8 hours). However, excessive sleep durations (≥9 hours) did not show a statistically significant association with prediabetes risk. Moreover, individuals at least 60years old who experienced short sleep durations exhibited a higher risk of prediabetes. Individuals with prediabetes were more likely to have shorter sleep duration than excessive sleep duration (relative risk ratios=1.280 [95% CI: 1.059-1.547]). The mediation analysis revealed a mediating effect of C-reactive protein on the association between prediabetes and reduced sleep duration.ConclusionsShort sleep duration was identified as a risk factor for the incidence of prediabetes. Conversely, prediabetes was found to contribute to shorter sleep duration rather than excessive sleep duration. Moreover, elevated levels of C-reactive protein may serve as a potential underlying mechanism that links prediabetes with shorter sleep.

The extent to which type 2 diabetes (T2D) reduces life expectancy depends on the risk of complications. We aimed to characterise the relationship between risk factors for diabetes complications and life expectancy, in individuals with T2D, free from major chronic disease, in a regional database linked with national New Zealand health databases. A prospective cohort study design was employed, analysing data from individuals with T2D drawn from the comprehensive Diabetes Care Support Service database (1994–2018). Participants with known values for all five within-target risk factors (WTRF +) including blood pressure, glycaemia, and LDL cholesterol, alongside being non-smoking with normal renal function at baseline, were included. Life expectancy free from cardiovascular disease (CVD), cancer, and dementia at age 50 years was estimated using multistate life tables, adjusting for demographics and clinical metrics. Women and men with no WTRF + at enrolment had a life expectancy free from CVD, cancer, or dementia of 13.1 (95

IntroductionTo evaluate the long-term risk of developing type 2 diabetes (T2D) among women with a history of gestational diabetes mellitus (GDM) compared with those with impaired glucose tolerance (IGT).Research design and methodsUsing data from a primary care dataset linked with multiple health registries, this longitudinal study analyzed demographics, clinical data, and lifestyle factors of women diagnosed with GDM or IGT, assessing T2D incidence over 25 years, using Cox regression models.ResultsWomen with GDM, especially those over 35 years of Māori ethnicity, or socioeconomic deprivation, exhibited an elevated risk of T2D compared with those with IGT. The first 5 years post partum emerged as a critical window for intervention.ConclusionsThis study underscores the importance of early, targeted post-GDM interventions to mitigate T2D risk. It highlights the necessity of personalized post-GDM interventions to reduce T2D incidence which consider age, ethnicity, and socioeconomic status to maximize effectiveness.

Big data and artificial intelligence technologies have played a positive role in the prevention and control of COVID-19 outbreaks.However,its application and future trends has not been comprehensively discussed.Starting from the problems faced by the prevention and control of COVID-19,this study provided an overview of the common big data and artificial intelligence technologies and their practical application cases in the prevention and control of COVID-19 based on the introduction of the advantages of big data and artificial intelligence technologies,then discussed the application of big data and artificial intelligence technologies focusing on three elements of infectious source,route of transmission and susceptible population from the three stages that before,during,and after the COVID-19 outbreak based on the Haddon model perspective.The results of the study are important for clarifying the positive role of big data and artificial intelligence technologies in each stage of COVID-19 epidemic as well as their directions of development and application,further improving the efficiency and quality of the prevention and control of COVID-19,and effectively responding to new infectious diseases in the future.

BACKGROUND:The prevalence of combinations of comorbidities and their associations with inpatient service utilization and readmission among patients with chronic obstructive pulmonary disease (COPD) have not been extensively examined. To address this gap in knowledge, an observational prospective study was conducted using retrospective data. AIMS:To identify patterns of comorbidities linked to length of hospital stay, daily expenses, and one-year readmission. METHODS:The 30 most common comorbidities were identified in patients with secondary diagnoses using the association rule mining (ARM) method. Regression models were used to examine the relationships between combinations of comorbidities and service utilization, with adjustments for covariates. RESULTS:The five most prevalent comorbidities were pulmonary heart disease (40.99%), ischemic heart disease (38.97%), heart failure (36.77%), hypertension (34.11%), and respiratory disorders (19.12%). Most combinations of comorbidities identified by ARM showed significant associations with an extended length of stay (>13 days), increased daily expenses (>930 CNY), and reduced readmission rates. Among these combinations, glycoprotein metabolism disorder had the strongest association with prolonged length of stay (adjusted odds ratio [aOR]): 1.89, 95% confidence interval [CI]: 1.82-1.95). Conversely, the combination of other brain diseases and respiratory failure was linked to higher daily expenses (aOR: 11.34, 95% CI: 10.58-12.15), and the presence of pulmonary heart disease was associated with elevated one-year readmission rates (aOR: 1.41, 95% CI: 1.37-1.46). CONCLUSION:Common combinations of comorbidities among inpatients with COPD were identified from an extensive collection of discharge medical records. Furthermore, the associations between comorbidities, inpatient service usage, and readmission rates were determined.

BACKGROUND:Lymphoma has become 1 of the 10 most common cancers with increased prevalence in young- and middle-aged adults in China. This poses a tremendous burden on patients and their families and brings great challenges to maintaining the balance of family functioning in young- and middle-aged patients. OBJECTIVE:This cross-sectional study aimed to analyse the influence of resourcefulness on the family functioning of Chinese young- and middle-aged lymphoma patients. METHODS:A total of 172 Chinese young- and middle-aged patients with lymphoma were recruited from the oncology departments of two tertiary hospitals in Zhengzhou, Henan, China. They were invited to complete a survey that included a demographic questionnaire, the Resourcefulness Scale and the Chinese Version Family Adaptability and Cohesion Scale II. Multiple linear regression was used to analyse the related factors for family functioning. RESULTS:The multiple regression analysis revealed that the main influencing factors of family cohesion were resourcefulness (β = 0.338, 95% CI (0.072, 0.173)), spouse caregiver (β = 0.376, 95% CI (1.938, 10.395)), and cancer stage (β = -0.274, 95% CI (-3.219, -1.047)). Resourcefulness (β = 0.438, 95% CI (0.096, 0.181)), spouse caregiver (β = 0.340, 95% CI (1.348, 8.363)), and family per capita monthly income (β = 0.157, 95% CI (0.066, 2.243)) were the influencing factors of family adaptability. CONCLUSIONS:Healthcare professionals and family scholars should value young- and middle-aged lymphoma patients' family functioning throughout the cancer treatment process, and family interventions should be designed by healthcare providers based on patients' resourcefulness. Moreover, healthcare providers need to pay attention to the risk factors of patients' family cohesion and adaptability, such as low family per capita monthly income, and consider employing corresponding measures to help them.

Background As life expectancy increases, so does the risk of age-related diseases and functional disability, which significantly raises the risk of all-cause mortality in older adults. Individuals with disabilities may die up to 20 years earlier than those who are non-disabled. Objectives To develop a prediction model for functional disability using random survival forest analysis (RSF). Methods Data were drawn from 2,364 older adults without functional disability from the China Health and Retirement Longitudinal Study (CHARLS), conducted from 2011 to 2020. Functional disability was the primary outcome. Univariable and multivariable Cox regression analyses were used to identify significant factors, which were then screened using variable importance (VIMP) and minimal depth to construct the RSF model. The model's performance was evaluated using calibration curves and the area under the receiver operating characteristic (AUC) curve. Multimorbidity trajectories were also identified as potential risk factors through group-based multi-trajectory modeling. Results Four multimorbidity trajectories were identified: no multimorbidity, newly-developing, moderate-developing, and severe-developing. The RSF model outperformed the Cox regression model in predicting functional disability, with key factors including age, education, walking time, grip strength, CES-D score, and multimorbidity trajectories. Significant factors identified were CES-D score, grip strength, multimorbidity trajectory, age, and the use of antihypertensive medications. Conclusions The RSF model, based on CHARLS data, effectively predicts functional disability in older adults, with depressive symptoms, handgrip strength, multimorbidity trajectories, age, and antihypertensive medication use emerging as key predictors.

Purpose:This study aims to investigate factors affecting medical personnel behavioral preferences for providing mHealth in China, so as to provide decision-making basis for mHealth providers and managers to encourage more doctors to participate in mHealth service delivery.Methods:Typical case sampling techniques were applied in a hospital setting to conduct a discrete choice experimental questionnaire survey of doctors (n=216) concerning mHealth preferences between July and October 2022. A conditional logit model was used to assess medical personnel preferences for each attribute and level of mHealth services.Results:Length of service, information security, subjects of treatment and financial compensation all have a significant effect on medical staff's preference for providing mHealth services (p < 0.05). In terms of service duration and financial compensation, medical staff preferred mHealth services that provided shorter service duration and higher financial compensation; in terms of information security, medical staff preferred mHealth services with confidentiality of diagnostic and therapeutic information compared to information disclosure; and in terms of treatment targets, medical staff preferred the general population compared to key populations, such as pregnant women, the elderly, infants and children.Conclusion:The preference of medical professionals to provide mHealth services is affected by a variety of factors. By enhancing the confidentiality of information in mHealth services, providing more options for service recipients, increasing their financial compensation, and shortening the duration of the service or increasing the number of service hours that can be adjusted can guide improvement of mHealth services and promoting of its adoption among medical professionals.

Objective:To explore the mediating effect of family function on the relationship between resourcefulness and psychological distress in young and middle-aged patients with lymphoma.Methods:The general information questionnaire, Resourcefulness Scale, Family Adaptation and Cohesion Evaluation ScaleⅡ,and Distress Thermometer were used to investigate young and middle-aged lymphoma patients in the oncology department of two tertiary hospitals in Zhengzhou from September to December 2021.Results:The scores of Resourcefulness Scale, Family Adaptation and Cohesion Evaluation ScaleⅡ,and Distress Thermometer of young and middle-aged lymphoma patients were 83.65±21.56,119.24±15.04 and 4.28±2.13,respectively.The resourcefulness of young and middle-aged patients with lymphoma was positively correlated with family function（r=0.444,P＜0.01）,was negatively correlated with psychological distress（r=-0.498,P＜0.01）,family function was negatively correlated with psychological distress（r=-0.827,P＜0.01）;Bootstrap results showed that family function had a complete mediating effect on the relationship between resourcefulness and psychological distress, and the mediating effect size was-0.43（95%CI:-0.171～-0.084）.Conclusion:Resourcefulness and family function are closely related to the psychological distress of lymphoma patients, and family function plays a complete mediating role in the relationship between resourcefulness and psychological distress.

目的:分析河南省公立医院老年人患病类型及结构变动情况,以制定有针对性的老年疾病主动防治干预策略.方法:收集河南省二级和三级公立医院 2016-2021 年老年人住院信息,并对疾病病种进行分类,采用结构变动度、结构变动值和结构变动贡献率等分析病种构成变动情况.结果:河南省老年人患病类型前4 顺位为脑血管病、缺血性心脏病、其他主要消化系统疾病(胃炎和十二指肠炎、胆和胰腺疾病和肠梗阻)和其他神经系统和精神障碍疾病(主要为短暂性大脑缺血性发作和相关的综合征),且顺位构成变化较小;前11 顺位疾病结构变动度为11.85%.缺血性心脏病、其他心血管疾病、慢性阻塞性肺疾病和脑血管病对疾病结构变动的累计贡献率为64.05%.结论:河南省老年人患病类型主要为心脑血管和消化系统疾病,应根据患病构成变化趋势和年龄分段情况,积极采取有针对性的疾病干预策略.

目的:基于复合系统协同度模型,测量医疗服务系统和公共卫生系统协同发展程度.方法:根据卫生资源配置评价相关指标,分别构建医疗服务系统(S1)和公共卫生系统(S2)的协同度评价框架;采集相关年鉴数据,测量2010-2020年S1和S2的有序度以及复合系统间的协同度.结果:2010-2020年,S1和S2内部的有序度和系统间的协同度均呈现快速上升态势;医疗-公卫复合系统的协同度先下降后快速上升,2020年达到一般协同状态(0.63).从不同序参量的结果看,每千人口床位数、万元以上设备数、房屋建筑面积在不同系统间稳步正向协同发展;每千人口卫技人员的协同水平较弱且波动较大;每千人口机构数则始终处于不协同状态.结论:2010年以来,S1和S2的有序度不断提升,复合系统的协同度不断增强;后续卫生资源配置规划中,需着重加强基层医疗机构的应急能力建设及系统间人力资源配置的协同,逐步探索将协同度分析引入卫生资源规划配置的新思路.

BACKGROUND:This study presented the mortality trend of ischemic heart disease (IHD) in Chinese residents from 2010 to 2019 and provided a basis for further establishment of relevant interventions. METHODS:Data, such as sex, age, urban and rural areas, and death status, were extracted from the China Death Surveillance Dataset from 2010 to 2019, with mortality and age-adjusted death rates (AADRs) as the main indicators. The joinpoint regression model was used to analyze mortality and AADRs trends in IHD. A semi-structured expert interview was conducted to propose targeted intervention measures and countermeasures. RESULTS:We observed an overall upward trend in IHD mortality rates and AADRs in China from 2010 to 2019 (average annual percentage change [AAPC] = 5.14%, AAPCAADRs = 1.60%, P < 0.001). Mortality rates and AADRs increased for both males (AAPC = 4.91%, AAPCAADRs = 1.09%, P < 0.05) and females (AAPC = 5.57%, AAPCAADRs = 1.84%, P < 0.001), with higher mortality rate for males than females but higher variation for females than males. Urban (AAPC = 4.80%, AAPCAADRs = 1.76%, P < 0.05) and rural (AAPC = 5.31%, P < 0.001; AAPCAADRs = 0.99%, P > 0.05) mortality rates increased, with the mortality rate higher in rural areas than in urban areas. In the age analysis, mortality rate was higher in middle-aged and older adults than in other age groups. The age-sex cross-analysis found the highest trend in mortality rates among females aged ≥ 75 years (annual percentage change [APC] = 2.43%, P < 0.05). CONCLUSIONS:The upward trend in IHD mortality in China from 2010 to 2019, especially among female residents aged ≥ 75 years, poses continuing challenges to public health policies and actions.

对主动健康的定义、特征与关键要素进行研究,能够丰富主动健康的理论体系.从健康风险因素出发,主动健康是以人民健康为中心,以优质医疗资源为引领,整合协调多领域、多学科、多机构的优势资源,围绕促进健康生活方式行为、打造健康生产生活环境、构建整合型医疗卫生服务体系所开展的社会活动的总和.实现主动健康需要从健全健康教育体系、构建主动健康政策环境、完善主动健康服务模式、发展大健康产业等方面持续发力.

目的 分析我国远程医疗协作网的建设以及运行情况,为推动远程医疗协作网可持续发展提供政策建议.方法 根据远程医疗协作网绩效考核评估指标建立"卫生健康政策评估信息系统",以2022年11月各远程医疗协作网牵头医院填报数据为研究资料;经数据清洗后,运用描述性统计分析方法,分析远程医疗协作网建设与运行情况.结果 2022年牵头医院中三级甲等医院占比为79.40%,每家牵头医院参与远程医疗的临床和医技专家数为205.35人和117.15人,每家牵头医院所属辖区内远程医疗协作网总覆盖率为11.74%;远程诊疗量占前5位的科室分别为医学影像、心血管内科、神经内科、呼吸内科、消化内科;每家牵头医院远程诊断和会诊量平均为14 921.06例和2 408.60例;按照有关要求执行当地政府制定的有关远程医疗价格标准与支付标准的牵头医院占比为71.05%.结论 政府应鼓励和引导实力较强的国家和省级医院及其临床和医技专家参与组建远程医疗协作网,提供更多优质医疗服务;优化远程医疗协作网内部管理规范和运行保障机制;完善远程医疗服务价格和费用报销机制,促进远程医疗协作网发挥优质医疗资源辐射和带动作用,助力分级诊疗.

目的:探讨郑州市中青年淋巴瘤患者智谋水平、心理一致感与家庭功能的关系,为制订相关干预措施提供依据.方法:采用一般资料调查表、智谋量表、家庭亲密度与适应性量表和心理一致感量表调查郑州市中青年淋巴瘤患者202 例.结果:中青年淋巴瘤患者智谋水平、家庭功能及心理一致感总分分别为(83.74±21.43)分、(119.42±15.21)分和(59.58±10.39)分.中青年淋巴瘤患者心理一致感总分与智谋水平总分、家庭功能总分均呈正相关(r=0.419、0.458,均P<0.01),智谋水平总分与家庭功能总分呈正相关(r=0.445,P<0.01).心理一致感是智谋水平与家庭功能间的中介变量,中介效应占总效应的 30.79%.结论:智谋水平可通过心理一致感影响中青年淋巴瘤患者的家庭功能,临床护理人员在重视提高患者智谋水平的同时应重视患者的心理一致感,提供针对性的支持以改善其家庭功能,促进患者康复.

External supervision is an important starting point to promote the comprehensive reform of public hospitals, and it is also a strong guarantee for the high-quality development of public hospitals. In this study, the first affiliated hospital of Zhengzhou University has sorted out and compared four external supervision measures, including re-examination and review of Grade Ⅲ Level A hospitals hospitals,medical institution verification, large-scale hospital inspection, and performance evaluation of Grade Ⅲ public hospitals, and found that At present, there are problems such as the lack of effective coordination between different regulatory measures, the regulatory model that needs to be optimized, the lack of initiative of large public hospitals in monitoring, and the degree of multi-departmental collaboration that still needs to be strengthened. It is recommended to improve the top-level design and coordinate various supervision measures; innovate working methods and optimize the external supervision mode; strengthen internal and external integration and establish a long-term working mechanism; emphasize the concept of integration and improve the level of hospital collaboration.