Health Indicators Research Articles

How much missing data is too much to impute for longitudinal health indicators? A preliminary guideline for the choice of the extent of missing proportion to impute with multiple imputation by chained equations

BackgroundThe multiple imputation by chained equations (MICE) is a widely used approach for handling missing data. However, its robustness, especially for high missing proportions in health indicators, is under-researched. The study aimed to provide a preliminary guideline for the choice of the extent of missing proportion to impute longitudinal health-related data using the MICE method.MethodsThe study obtained complete data on five mortality-related health indicators of 100 countries (2015–2019) from the Global Health Observatory. Nine incomplete datasets with missing rates from 10 to 90% were generated and imputed using MICE. The robustness of MICE was assessed through three approaches: comparison of means using the Repeated Measures- Analysis of variance, estimation of evaluation metrics (Root mean square error, mean absolute deviation, Bias, and proportionate variance), and visual inspection of box plots of imputed and non-imputed data.ResultsThe Repeated Measures- Analysis of variance revealed significant differences between complete and imputed data, primarily in imputed data with over 50% missing proportions. Evaluation metrics exhibited ‘high performance’ for the dataset with a 50% missing proportion for various health indicators However, with missing proportions exceeding 70%, the majority of indicators demonstrated a ‘low’ performance level in terms of most evaluation metrics. The visual inspection of the box plot revealed severe variance shrinkage in imputed datasets with missing proportions beyond 70%, corroborating the findings from the evaluation metrics.ConclusionIt demonstrates high robustness up to 50% missing values, with marginal deviations from complete datasets. Caution is warranted for missing proportions between 50 and 70%, as moderate alterations are observed. Proportions beyond 70% lead to significant variance shrinkage and compromised data reliability, emphasizing the importance of acknowledging imputation limitations for practical decision-making.

A novel intelligent health indicator using acoustic waves: CEEMDAN-driven semi-supervised ensemble deep learning

Designing health indicators (HIs) for aerospace composite structures that demonstrate their health comprehensively, including all types of damage that can be adaptively updated, is challenging, especially under complex conditions like impact and compression-fatigue loadings. This paper introduces a new AI-based approach to designing reliable HIs (fulfilling requirements—monotonicity, prognosability, and trendability—referred to as ’Fitness’) for single-stiffener composite panels under fatigue loading using acoustic emission sensors. It incorporates complete ensemble empirical mode decomposition with adaptive noise for feature extraction, semi-supervised base deep learner models made of long short-term memory layers for information fusion, and a semi-supervised paradigm to simulate labels inspired by the physics of progressive damage. In this way, nondifferentiable prognostic criteria are implicitly implemented into the learning process. Ensemble learning, especially using a semi-supervised network built with bidirectional long short-term memory, improves HI quality while reducing deep learning randomness. The Fitness function equation has been modified to provide a more trustworthy foundation for comparison and enhance the practical reliability of the standard in prognostics and health management. Ablation experiments are conducted, including variations in dataset division and leave-one-out cross-validation, confirming the generalizability of the approach.

Linking Multi-Dimensional Religiosity in Childhood and Later Adulthood: Implications for Later Life Health.

This study examines religiosity patterns across childhood and later adulthood and their associations with later-life health using an experimental module from the 2016 Health and Retirement Study (N = 1649; Mean Age = 64.0). Latent class analysis is used to categorize individuals by commonalities in religious attendance, religious identity, and spiritual identity. Cross-sectional and longitudinal associations are then explored using probable depression, disability, and mortality as health indicators. Results reveal complex patterns, often characterized by declining attendance and fluctuating identity. Relationships with health appear stronger in cross-sectional analyses, suggesting that some associations may be non-causal. Individuals with consistently strong religiosity show significantly better psychological health compared to their relatively non-religious counterparts. Moreover, the absence of religiosity in later adulthood is associated with an increased risk of mortality. Overall, the findings support the promotion of religiosity whilst acknowledging individual variations and highlighting the need for more individualistic approaches to the study of religion and health.

"Listening to understand," exploring postpartum women's perceptions of their social networks and social support in relation to their health behaviors and weight: A qualitative exploratory study.

Postpartum is a critical period to interrupt weight gain across the lifespan, decrease weight-related risk in future pregnancies, promote healthy behaviors that are often adopted during pregnancy, and improve long-term health. Because the postpartum period is marked by unique challenges to a person's ability to prioritize healthy behaviors, a multi-level/domain approach to intervention beyond the individual-level factors of diet and activity is needed. The purpose of this study was to understand postpartum people's perceptions about the relationship between their social networks and support, and their health behaviors and weight. We used a qualitative descriptive approach and in-depth interviews. Participants (aged 18+, 12-15 months postpartum, who had a pre-pregnancy body mass index ⩾25) engaged in one-on-one, in-depth interviews conducted via Zoom (n = 28). Additional qualitative data came from open-ended responses to an online survey (n = 84) and a personal social-network survey (n = 84). Qualitative analysis used content and thematic analysis in stages of deductive coding applying codes derived from social-network and support theories, followed by inductive coding. Thirty-eight participants (38.4%) returned to or weighed less than pre-pregnancy weight. We identified two overarching themes grounded in social-network and support theories. They were: (1) normative influence impacts health behaviors, body image, and experiences of weight stigma, and (2) network social support is related to health goals and overall postpartum health. Postpartum networks/support hindered and supported participants' goals. Partners provided an important source of accountability but were often associated with barriers to healthier behaviors. Our findings reinforce the importance of the social context when considering how to support healthy behaviors and weight during the postpartum period. Healthcare providers should focus on health indicators other than maternal weight, and those wishing to support healthy postpartum behaviors could focus on child and family health, rather than solely on maternal weight and health behaviors.

Is trauma associated with plant-based diet choice?

Examinations of links between plant-based diets (e.g., vegetarian and vegan diets) and indices of physical and mental health have received increased attention in the scientific literature in recent years. However, there has been little to no published research examining predictors of plant-based diet choice. Researchers have suggested that plant-based diets could be linked to trauma for a variety of reasons, including the idea that trauma can increase the risk for mental illnesses, and plant-based diets may be adopted to self-medicate mental illness and promote recovery. The current study examined the link between trauma across the lifespan and experiences of intimate partner violence (IPV) with adherence to a plant-based diet. Participants were a nationally representative United States sample of 1665 individuals who completed self-report questionnaires. Consistent with hypotheses, bivariate correlations indicated that all measures of trauma were associated with an increased likelihood of being plant-based. Findings from a logistic regression analysis indicated those with a history of IPV were 2.31 times more likely to be plant-based, and those with any experience of trauma more broadly were 1.09 times more likely to be plant-based. These results suggest the importance of considering the role of trauma and victimization when examining links between plant-based diet and other outcomes and point to a number of possible avenues for additional investigation to better understand these associations.

Epidemiology of menstrual-related absenteeism in 44 low-income and middle-income countries: a cross-sectional analysis of Multiple Indicator Cluster Surveys.

Menstrual-related absenteeism from work, school, or social activities is an important functional indicator of poor menstrual health that disrupts women's and girls' daily lives and exacerbates gender inequality. We sought to estimate the prevalence of and factors contributing to menstrual-related absenteeism across low-income and middle-income countries. We analysed cross-sectional data from 47 nationally or subnationally representative Multiple Indicator Cluster Surveys from 2017 to 2023, which comprised 3 193 042 individuals from 555 869 households across 44 countries; those with available information on the outcome of interest were included in our analysis. The outcome of interest was menstrual-related absenteeism from work, school, or social activities during the respondent's last menstrual period. Independent factors included age, household wealth index, use (vs no use) of menstrual materials (eg, pads, tampons, or cloth), availability of a private place to wash at home during menstruation, and contraceptive use (hormonal and other). Univariable and multivariable associations between each factor and menstrual-related absenteeism were analysed using log-binomial models. Prevalence ratios, estimated from the log-binomial models, represent the relative prevalence of menstrual-related absenteeism across different levels of the independent variables. Prevalences and associations were pooled by geographical region and overall across all surveys using a random-effects meta-analysis. Heterogeneity was assessed using the I2 statistic, and prediction intervals generated to reflect the variation in associations. We included 673 380 women and girls aged 15-49 years in this analysis. The overall pooled prevalence of menstrual-related absenteeism was 15·0% (95% CI 12·7-17·3), with prevalence being highest in south Asia (19·7% [11·6-27·8]) and west and central Africa (18·5% [13·5-23·5]). After pooling data across surveys, girls aged 15-19 years were found to have a higher prevalence of menstrual-related absenteeism than those in older age groups, with overall pooled prevalence ratios ranging from 0·75 (0·68-0·82) in those aged 35-39 years to 0·92 (0·87-0·97) in those aged 20-24 years relative to the 15-19 years age group, with adjustment for area type (urban or rural). There was no association between menstrual-related absenteeism and household wealth or the use of menstrual materials. By contrast, having a private place to wash at home was associated with an increased prevalence of menstrual-related absenteeism (overall pooled prevalence ratio 1·25 [1·05-1·48], adjusted for wealth and area type). Menstrual-related absenteeism was less prevalent in women and girls using any contraceptives compared with those not using contraceptives (0·92 [0·87-0·96]), and for those using hormonal contraceptives compared with those using non-hormonal or no contraceptives (0·91 [0·84-0·99]), after adjusting for age, wealth, education level, parity, and area type. Menstrual-related absenteeism is prevalent, especially in Asia and Africa and among adolescent girls. The age-independent protective effect of hormonal contraceptive use suggests that symptoms such as heavy menstrual bleeding or pain contribute to absenteeism. Future studies are urgently needed to better characterise these findings to inform relevant public health interventions. National Health and Medical Research Council, Australia.

Assessment of macrobenthos in evaluating the restoration effects of artificial mangrove planting on tidal flats in Zhejiang, China.

Artificially planted mangroves are widely used for tidal flat restoration, but their effectiveness in restoring these ecosystems remains unclear. Macrobenthos, as key indicators of tidal flat ecosystem health, can reflect changes in environmental conditions and quality resulting from the introduction of artificial mangroves. This study aimed to investigate the ecological restoration effects of artificially planted mangroves in northern China by surveying macrobenthic communities across four regions in June 2023. We compared the macrobenthic community structures in mangrove zones with those in Spartina alterniflora or unvegetated mudflat control zones by estimating habitat quality indices and community structure analyses. Additionally, we explored the relationship between community structures and environmental factors to identify key drivers of community structure changes. Significant differences in species abundance and biomass were observed across the four regions, with mudflat zones exhibiting the highest values, followed by mangrove and Spartina alterniflora zones. Beta diversity was higher in mangrove zones compared to control zones, driven primarily by turnover components. The AMBI index indicated excellent ecological conditions in 18-year-old mangrove zone on Maoyan Island, while poorer conditions were observed in the mangrove zone of Zhoushan City. Environmental factors, such as sand content, organic carbon content, and elevation, significantly influenced macrobenthic community distribution. Overall, our findings suggest that the 18-year-old mangrove zone on Maoyan Island is ecologically stable and demonstrates significant restoration effects. Using macrobenthos to assess the restoration efficacy of mangroves proves to be both effective and feasible. Furthermore, while the mangroves have successfully established and grown, their long-term survival depends on the active involvement of local stakeholders, highlighting the importance of long-term monitoring and adaptive management strategies.

Developing predictive models for assessing LC50 of organic contaminants in Gammarus species using interpretable structural parameters.

Gammarus species are crucial indicators of environmental health, making them important for ecological studies and water quality assessments. They offer a wide range of specific responses regarding the median lethal concentration (LC50) of organic compounds. This research presents four predictive models to determine the LC50 of chemicals impacting selected gammarid amphipods: Gammarus lacustris, Gammarus fasciatus, Gammarus pulex, and Gammarus pseudolimnaeus. These species are recognized for their sensitivity to various pollutants and are among the most sensitive aquatic invertebrates. The new models provide straightforward methods for estimating the pLC50 (-log LC50/molecular weight) of various organic compounds based on interpretable structural parameters including the number of effective functional groups, the types of atoms present, and various structural characteristics of organic molecules. This study aims to leverage the largest available experimental dataset compared to prior quantitative structure-activity relationship (QSAR) models for these gammarid amphipods. The dataset contained toxicity data for 91 compounds affecting Gammarus fasciatus, 50 for Gammarus lacustris, and 48 each for Gammarus pseudolimnaeus and Gammarus pulex, aligning with comparative QSAR models. External datasets included 13 compounds for Gammarus fasciatus, 2 for Gammarus lacustris, and 6 for Gammarus pseudolimnaeus. Efforts focus on using interpretable structural parameters of organic compounds rather than computer-based descriptors, as outlined in the existing QSAR models. For the species G. fasciatus, G. lacustris, G. pseudolimnaeus, and G. pulex, the R² ratios for the new models versus the best QSAR models are 0.915/0.728, 0.955/0.747, 0.976/0.769, and 0.970/0.768, respectively. The higher R² values in the new models demonstrate greater reliability and robustness in capturing the data's underlying relationships.

Gene Therapy for Skin Aging.

Extrinsic and intrinsic factors contribute to skin aging; nonetheless, they are intertwined. Moreover, intrinsic skin aging mirrors age-related declines in the entire human body's internal organs. There is evidence that skin appearance is an indicator of the general health of somebody or a visual certificate of health. Earlier, it was apparent that the intrinsic factors are unalterable, but the sparkling of skin aging gene therapy on the horizon is changing this narrative. Skin aging gene therapy offers tools for skin rejuvenation, natural beauty restoration, and therapy for diseases affecting the entire skin. However, skin aging gene therapy is an arduous and sophisticated task relying on precise interim stimulation of telomerase to extend telomeres and wend back the biological clock in the hopes to find the fountain of youth, while preserving cells innate biological features. Finding the hidden fountain of youth will be a remarkable discovery for promoting aesthetics medicine, genecosmetics, and healthy aging. Caloric restriction offers ultimate health benefits and a reproducible way to promote longevity in mammals, while delaying age-related diseases. Moreover, exercise further enhances these health benefits. This article highlights the potential of skin aging gene therapy and foretells the emerging dawn of the genecosmetics era.

Environmental contaminants assessment for frequently harvested migratory waterfowl in the Northeast Atlantic flyway.

Waterfowl serve as indicators of ecosystem health and represent a pathway of contaminant exposure for hunters who consume them. In the northeast Atlantic Flyway, data on baseline contaminant loads in waterfowl are lacking. We assessed five species of commonly harvested (and consumed) waterfowl for mercury, polychlorinated dibenzo-p-dioxins and polychlorinated dibenzofurans, polychlorinated biphenyls (PCBs), organochlorine pesticides (OCPs), and per- and polyfluoroalkyl substances (PFAS). We found that Canada geese (Branta canadensis) and wood ducks (Aix sponsa) had lower contaminant burdens than mallards (Anas platyrhynchos), American green-winged teal (Anas carolinensis), and American black ducks (Anas rubripes). Regardless of species, all samples contained detectable levels of PCBs and at least one OCP and PFAS. Mercury and OCPs posed limited non-cancer risks to human consumers who follow current waterfowl consumption advisories. Based on a probabilistic risk assessment, lower consumption rates were required to reduce risks from PCBs compared to other contaminants. Protective human consumption advisories depend in part on the level of allowable cancer risk and whether contaminants were considered toxicologically to act individually or collectively. Accordingly, revisions to consumption advisories to protect public hunter health given these new data hinge upon risk management decisions. These data can be used to update waterfowl consumption advisories in the northeast Atlantic Flyway and inform future research into the health effects of legacy and contemporary contaminants on the sustainability of waterfowl populations.

Longitudinal relations among online social activities, peer relationship problems, and well-being in children: The moderating effect of extraversion.

Prior research has predominantly examined the relations between online social activities (OSA) and mental health among adolescents and adults, with comparatively less emphasis placed on children, particularly concerning positive indicators of subjective health, such as well-being. The relations between OSA and well-being are likely intricate and necessitate meticulously designed methodologies to investigate the associations and their underlying mechanisms. This longitudinal study employed the random intercept cross-lagged panel models to explore the dynamic relations between OSA and well-being, considering peer relationship problems as a potential mediator and extraversion as a moderator of the associations, while distinguishing between- and within-person effects. A total of 2,300 Chinese children (56.1% boys, Mage = 9.49, SD = 0.56) completed four measurements over a two-year period. The results indicated that: (a) OSA negatively predicted well-being, but not vice versa; (b) peer relationship problems mediated the relations from OSA to well-being; and (c) extraversion served as a moderator of the associations, with notable differences between extraverted and introverted children. These findings provide valuable insights for developing targeted guidance for children's Internet use to enhance their general well-being.

Validating the questionnaire of achievement of developmental task (QADT) to measure achieving mental wellness in school-aged children.

This article presents a verification of the factor structure and validation of the Questionnaire of Achievement of Developmental Task (QADT), designed to measure children's social expectations in early childhood. Three tasks, important from the point of view of both children's functioning at a given life stage and preparation for the next developmental phase, were selected. These are school skills, cooperation with others and a sense of competence. The research aimed to verify the tool's psychometric validity and establish relationships between developmental tasks and indicators of children's mental health. The study was conducted in primary school's 4th, 5th and 6th grades (N = 453). The QADT, Brief Multidimensional Students' Life Satisfaction Scale and Center for Epidemiological Studies Depression Scale for Children were used. The tool shows sufficient validity and reliability. The hypothesis regarding associations between the level of developmental task completion and life satisfaction and depressive symptoms was also confirmed. The QADT tool can be used in scientific research. This work contributes to the growing body of literature on factors influencing children's mental health and underscores the importance of measuring social expectations of children in early childhood. It also highlights the need to consider developmental tasks in clinical practice and interventions to improve children's mental health. Ultimately, the findings of this study can inform the development of effective preventive and intervention strategies to promote children's mental health and well-being.

Dual jeopardy for Indian service users: Qualitative study of managing comorbid schizophrenia and diabetes mellitus.

Diabetes mellitus is a sequelae of antipsychotic medication in people of Indian descent with schizophrenia. The Indian socio-cultural context amplifies challenges of managing chronic illness. The aim of this study was to explore Indian mental health service users' perspectives of managing comorbid psychosis and diabetes mellitus, specifically culture-related difficulties. In this exploratory study, people with an Indian cultural background recruited from community mental health clinics were interviewed by an Indian psychiatrist using a semi-structured questionnaire. Interviews were professionally transcribed. Reflexive thematic analysis was used to develop central organising concepts and identify themes. Four themes were identified: culture-specific views on comorbidity, preferences for tailoring education to Indian language and culture, changes in interpersonal relationships within extended family and relationships with healthcare professionals. Advice from hospital services was not specific to Indian culture and there were wider impacts of illness for wider family. Indian New Zealanders have challenges in managing dual mental and physical illnesses. Further research is needed to develop approaches to care that emphasise service users' culture as core to understanding illness and treatment. This includes consideration of gender roles, families, communities, food, language, lifestyle and barriers to treatment.

The prevalence of hypoxaemia in paediatric and adult patients in health-care facilities in low-income and middle-income countries: a systematic review and meta-analysis.

Hypoxaemia (low oxygen saturation in blood) is a key predictor of in-hospital mortality, affecting people of all ages with many different conditions. Early detection and treatment of hypoxaemia are critical, but there are few data to quantify hypoxaemia burden outside the child pneumonia population. We aimed to estimate hypoxaemia prevalence for adults and children with acute illness attending health facilities in low-income and middle-income countries (LMICs). We conducted a systematic review and meta-analysis, searching MEDLINE, PubMed, Embase, Cumulated Index in Nursing and Allied Health Literature, Index Medicus, and Google Scholar for studies reporting hypoxaemia prevalence among patients attending health facilities. We included articles with original data on peripheral blood oxygen saturation (SpO2), from an LMIC, published between Jan 1, 1998, and Jan 10, 2023. We included studies in acutely unwell people of any age and with any condition, but excluded those admitted to intensive care units, receiving perioperative care, or attending hospital for preventive or chronic care. We assessed study quality using Joanna Briggs Institute's Checklist for Prevalence Studies. Two reviewers independently conducted title and abstract screening, full-text review, data extraction, and quality assessment, requesting summary data from authors. We reported pooled prevalence of hypoxaemia (typically defined as SpO2 <90%) overall and by condition, using a random-effects meta-analysis model. This study is registered with PROSPERO, CRD42019136622. We identified 9173 unique records from searches and included 213 in meta-analyses involving 601 757 participants. The majority of studies were from the World Bank regions of sub-Saharan Africa (108 [51%] of 213) or south Asia (58 [27%]). The pooled prevalence of hypoxaemia among admitted patients was 24·5% (95% CI 19·9-29·4) for neonates (aged 0-28 days), 12·1% (10·0-14·4) for children (aged 1 month-17 years), and 10·8% (4·9-18·7) for adults (aged ≥18 years). Hypoxaemia prevalence was highest in neonatal and primary respiratory conditions but still common in many other conditions. Hypoxaemia was associated with 4·84 (95% CI 4·11-5·69) times higher odds of death than no hypoxaemia. Hypoxaemia is common across all age groups and a range of primary respiratory and other critical illnesses and is strongly associated with death. These estimates will inform oxygen-related strategies and programmes, and integration of pulse oximetry and oxygen into clinical guidelines, service structures, and strategies for maternal, neonatal, child, adolescent, and adult health. Bill & Melinda Gates Foundation, the ELMA Foundation, and Unitaid.

Does a Small Country Have Meaningful Regional Personality Differences? The Case of Estonia.

Regional differences in the Big Five personality domains have been observed in several countries at different geographical granularities, often correlating with regional political, economic, social, and health (PESH) indicators. We examined the extent of regional personality differences in Estonia and whether these differences were meaningfully correlated with PESH indicators. Using data from the Estonian Biobank (N = 72,268; 7% of the adult population, providing unprecedented representativeness), we tested regional personality differences and their relations with PESH indicators with and without spatial smoothing. We found that regional Big Five scores varied by 1.19 (extraversion) to 2.78 (openness) T-score units across counties (N = 15) and by 2.80 (extraversion) to 4.74 (openness) units across municipalities (n = 74). Also, the correlations with the PESH indicators at the county and municipality levels persisted even after controlling for gender, age, and spatial dependency, and were moderately consistent with our predictions (r = 0.23 to 0.30) and between the county and municipality levels (r = 0.41). Estonian residents tended to be similar in personality traits regardless of their location, replicating results from other countries. Yet, small regional personality domain differences could represent valid and possibly consequential psychological variation.

Animal welfare assessment after controlled cortical impact in CD-1 mice - A model of posttraumatic epilepsy.

The ethical use of laboratory animals requires that the benefits of an experimental study are carefully weighed against potential harm to the animals. In traumatic brain injury (TBI) research, ethical concerns are especially relevant to severe TBI, after which animals may experience suffering, depending on the implementation of refinement measures such as (1) postsurgical analgesia during the initial period following TBI and (2) humane endpoints. However, despite the frequent use of rodent models such as fluid percussion injury (FPI) and controlled cortical impact (CCI) in rats or mice, there is only one recent study that applied assessment of welfare to a severe TBI model, the FPI model in rats. In the present pilot study in a CCI mouse model of posttraumatic epilepsy, we assessed animal welfare by a brain injury-specific severity scoresheet. Furthermore, nest building was used as a sensitive indicator of health and welfare in laboratory mice. Sham mice that underwent craniotomy but not CCI were used for comparison. Craniotomy and CCI were performed under anesthesia with isoflurane, followed by 3days of postsurgical analgesia with the opioid l-methadone. Mannitol was used to prevent the head pain caused by increased intracranial pressure. Using the TBI-specific scoresheet to describe and monitor potential distress in animals, moderately increased scores were determined in CCI mice only over the first 2days after surgery, indicating that animal suffering in this model is transitory. Similarly, significantly impaired nest building was observed at 1 but not 7days after CCI. We conclude that with effective postsurgical analgesia and mannitol behavioral recovery is rapid in mice after CCI.

The Associations Between Sleep Duration and Various Metabolic Health Indices Among Adults in the United States: A Multivariate Analysis of Variance (MANOVA) Using National Health and Nutrition Examination Survey (NHANES) 2021 to 2023 Dataset.

This study explores the associations between various sleep durations and metabolic health indices, including systolic blood pressure (SBP), diastolic blood pressure (DBP), total cholesterol levels, high-density lipoprotein (HDL) cholesterol, and waist circumference. Data from the National Health and Nutrition Examination Survey (NHANES) 2021 to 2023, were analyzed. MANOVA and Bonferroni-adjusted ANOVAs were conducted to examine the relationships between sleep duration (sleep deprivation (≤5 h), short sleep (5-7 h), recommended sleep (7-9 h), and long sleep (>9 h)) and metabolic health indices. MANOVA revealed significant group differences between sleep duration and metabolic health indices, with Wilks' Lambda (Λ) = .98, F (3, 5095) = 4.26, P < .001. Compared to recommended sleep duration, both sleep deprivation and short sleep were associated with higher DBP (Ps < .01) and waist circumference (Ps < .001), and lower HDL levels (Ps < .05) Long sleep was associated with lower HDL levels (P < .01) and lower total cholesterol (P < .01). The study highlights the detrimental associations of both sleep deprivation and short sleep with metabolic health, such as elevated blood pressure and waist circumference, and lowered HDL cholesterol. Long sleep may also negatively impact metabolic health by reducing HDL.

Oral Frailty Indicators and Cardio- and Cerebrovascular Diseases in Older Age:A Systematic Review

Oral health indicators may contribute to the oral frailty phenotype, an age-related gradual loss of oral function together with a decline in cognitive and physical functions. The present systematic review synthetized current knowledge on the associations of oral frailty indicators and major cardio- and cerebrovascular diseases in older age, including coronary heart disease (CHD), arteriosclerosis, arrhythmias, hypertension, cardiovascular diseases not otherwise specified (NOS), and stroke. The study is registered on PROSPERO-(CRD42023397932). From database inception to March 31, 2024, six different electronic databases were consulted assessing the eligibility of 50,005 records against the inclusion criteria and 20 studies on 226,025 older adults were included. Five different indicators of oral frailty (number of teeth, periodontal disease, general oral health, dry mouth, and bite force) were related to cardio- and cerebrovascular diseases. The number of teeth was associated with all the outcomes except hypertension, followed by periodontal disease associated with CHD, arteriosclerosis, hypertension, and stroke. General oral health and dry mouth were associated with CHD/arrhythmias and CHD/stroke, respectively. Finally, bite force was associated only with cardiovascular diseases NOS. The present findings could help to assess the contribution of each oral frailty indicator to the development of cardio- and cerebrovascular diseases in older age.

Health indicator construction and health status evaluation for the photovoltaic array based on the current–voltage curve conversion

Health indicator construction and health status evaluation for the photovoltaic array based on the current–voltage curve conversion

Capacity estimation of lithium-ion battery through interpretation of electrochemical impedance spectroscopy combined with machine learning

Lithium-ion batteries inevitably undergo degradation over extended use, making precise capacity estimation essential for reliable state monitoring and health prognostics. However, conventional capacity estimation methods, which rely predominantly on time-domain information, offer limited insights due to the complex degradation mechanisms intrinsic to lithium-ion batteries. Accordingly, a capacity estimation approach leveraging partial frequency electrochemical impedance spectroscopy data integrated with machine learning is proposed. A reconstructed simplified fractional-order model characterized by a minimal set of parameters and superior fitting performance is introduced to extra health indicators from EIS measurement. Detailed equivalent circuit parameter extraction is performed, and subsequently incorporated into an enhanced Gaussian process regression model for capacity estimation. The proposed approach is validated using datasets derived from real-driving profiles including comprehensive comparisons, demonstrating its feasibility and effectiveness. Experimental results confirm that the framework achieves high estimation accuracy, strong generalization, and robust performance, even in scenarios with limited data availability and training noise presence, with a root mean square error not exceeding 0.81 %, a mean absolute error below 0.62 %, and a maximum absolute error of no more than 0.0653 Ah.