Category: Statistics

Front Pediatr. 2026 Aug 14;14:1884107. doi: 10.3389/fped.2026.1884107. eCollection 2026.

ABSTRACT

BACKGROUND: Pediatric acute respiratory tract infections bring heavy global disease burden. Clarifying post-pandemic epidemiological features guides clinical management and public health prevention.

METHODS: This retrospective study enrolled patients under 18 years receiving 13-pathogen multiplex PCR at West China Second University Hospital from 2023 to 2025. We extracted laboratory data and calculated pathogen positivity, single/co-infection proportions. Stratified analyses by year, season, age and sex and statistical collation of co-infection patterns were completed.

RESULTS: In total, 32,125 children were included. The total pathogen positive rate reached 63.4%, including 49.8% single infection and 13.6% co-infection dominated by dual infection. Human rhinovirus (22.9%) ranked first, followed by respiratory syncytial virus (15.2%). Pathogens varied obviously across seasons and ages: HRV surged in spring and autumn; parainfluenza, adenovirus and coronavirus prevailed in summer; syncytial virus and influenza peaked in winter. Respiratory syncytial virus mainly affected infants; rhinovirus and parainfluenza were prevalent in toddlers and preschoolers; Mycoplasma pneumoniae rose with age and peaked among school-age children. Dual infection occupied nearly all co-infections; the top non-influenza combinations were HRSV-HRV and HRV-HAdV. Infections with three or more pathogens were rare.

CONCLUSIONS: HRV and HRSV dominated pediatric respiratory pathogens with obvious seasonal and age clustering. Most co-infections occurred in winter and young kids. HRV detection requires careful explanation for potential asymptomatic carriage. Local epidemiological characteristics should inform age-and seasonal-targeted diagnosis and targeted prevention including HRSV prevention.

PMID:42666339 | PMC:PMC13522108 | DOI:10.3389/fped.2026.1884107

Front Nutr. 2026 Aug 14;13:1902694. doi: 10.3389/fnut.2026.1902694. eCollection 2026.

ABSTRACT

OBJECTIVE: To examine associations between objectively quantified tongue features and the Controlling Nutritional Status (CONUT) score in patients with diabetic kidney disease (DKD), and to assess the influence of renal function and glycaemic status on these associations.

METHODS: This dual-centre cross-sectional study included 392 patients with DKD. Fifty-one tongue features were extracted using the YZAI-02 AI tongue imaging system. CONUT was calculated from serum albumin, lymphocyte count, and total cholesterol after multiple imputation by chained equations (m = 20). Rubin-pooled partial Spearman correlations, adjusted single-feature and joint multivariable linear regression, sensitivity analyses, and ordinal logistic regression were performed. Covariates were selected a priori and included age, sex, study centre, estimated glomerular filtration rate (eGFR), and HbA1c. Exploratory stratified and interaction analyses were conducted according to eGFR and sex.

RESULTS: The median CONUT score was 3 (interquartile range: 2-5), and 304 patients (77.6%) had CONUT-defined malnutrition. Five of 51 tongue features reached nominal significance in partial-correlation screening, although none survived false discovery rate correction across all 51 comparisons. After collinearity pruning, five representative features met the exploratory false discovery rate threshold in adjusted single-feature models. In the joint multivariable model, higher edge tongue saturation (β = 0.269 per standard deviation, 95% CI: -0.023 to 0.560, p = 0.071) and lower middle tongue brightness (β = -0.234, 95% CI: -0.495 to 0.026, p = 0.078) showed borderline associations with higher CONUT scores. Adding eGFR increased the coefficient for edge tongue saturation from 0.131 to 0.289, consistent with statistical suppression, whereas the coefficient for middle tongue brightness remained stable. Additional proteinuria adjustment produced coefficient changes below 15%, and both estimates remained imprecise. In ordinal logistic regression, edge tongue saturation showed a directionally consistent borderline association (OR = 1.29, 95% CI: 0.96-1.71, p = 0.086). No interaction remained significant after false discovery rate correction.

CONCLUSION: CONUT-defined malnutrition was common in DKD. Middle tongue brightness and edge tongue saturation showed modest, borderline associations with nutritional risk, suggesting that AI-assisted tongue phenotyping warrants further evaluation as a complement to nutritional surveillance in DKD.

PMID:42666325 | PMC:PMC13521857 | DOI:10.3389/fnut.2026.1902694

Front Psychol. 2026 Aug 14;17:1841408. doi: 10.3389/fpsyg.2026.1841408. eCollection 2026.

ABSTRACT

OBJECTIVE: To explore the improvement effect of lower limb exoskeleton robot intervention on the athletic performance of disabled athletes and the underlying psychological mechanisms, so as to provide empirical evidence and theoretical support for clinical application.

METHODS: Thirty disabled athletes with lower limb motor dysfunction were selected for a 12-week randomized controlled trial. Data before and after intervention were collected through athletic performance tests, psychological scale assessments and semi-structured interviews. Statistical analysis was performed using SPSS, and qualitative data were combined to explore the action pathways of psychological mechanisms.

RESULTS: After intervention, the athletic performance indicators of the experimental group were significantly higher than those of the control group; the scores of self-efficacy and intrinsic sports motivation in the experimental group were significantly increased, while the scores of anxiety and depression were significantly decreased, and there was a significant correlation between psychological indicators and athletic performance indicators. Qualitative analysis showed that lower limb exoskeleton robots indirectly promoted athletic performance through four psychological mechanisms: reducing sports frustration, enhancing body control, improving self-identity, and relieving psychological pressure.

CONCLUSION: Lower limb exoskeleton robots can improve the athletic performance of disabled athletes by improving their psychological state.

PMID:42666311 | PMC:PMC13521860 | DOI:10.3389/fpsyg.2026.1841408

Front Public Health. 2026 Aug 14;14:1908891. doi: 10.3389/fpubh.2026.1908891. eCollection 2026.

ABSTRACT

BACKGROUND: Framework health legislation is increasingly used to codify government responsibility, health-promotion duties, and accountability for basic services, yet it is difficult to identify whether such laws produce measurable economic and health effects. China’s Basic Medical and Health Care and Health Promotion Law, effective June 2020, consolidated these duties in a single national statute.

METHODS: Using a province-year panel for 31 mainland provinces over 2015-2022 compiled from public statistical yearbooks, we evaluate the law with a differential-bindingness difference-in-differences (DID) design: because the statute applies nationwide, treatment is defined ex ante as provinces below the median of a frozen 2015-2019 public-health-capacity index, for which the law is expected to be more binding. The compiled data do not contain annual provincial maternal or infant mortality, so the executed analysis uses the health outcomes that are actually observed-crude population mortality, emergency case-fatality and observation-room case-fatality in medical institutions, outpatient health checkups per resident, and average hospital length of stay. These are availability-driven proxies, not the ideal outcomes.

RESULTS: The most consistent association is a relative post-law decline in emergency case-fatality in high-bindingness provinces (about -0.03 percentage points, p < 0.05 in the full model); its magnitude is stable across pandemic-sensitivity checks, but statistical significance weakens when 2022, the most coronavirus disease 2019 (COVID-19)-disrupted year, is excluded. The crude-mortality estimate is suggestive but fragile: it is significant only with full controls (p ≈ 0.06), is attenuated under matching, and reverses sign under a fiscal-capacity-based treatment definition. Mechanism tests reveal no robust mediator through fiscal, staffing, or institutional channels; only outpatient checkups respond marginally. Event-study diagnostics do not reject parallel pre-trends, but the short post-law window and 31 clusters limit precision.

CONCLUSION: We find suggestive, definition-sensitive evidence that framework health law may be associated with modest differential gains in some service-quality outcomes where pre-law capacity was weaker. Still, the data cannot support strong causal claims, and post-law shifts cannot be fully separated from province-specific COVID-19 dynamics. The contribution is a transparent, reproducible evaluation scaffold and a cautionary finding: detecting the economic effects of health legislation requires better subnational outcome reporting, especially maternal and infant mortality.

PMID:42666302 | PMC:PMC13522156 | DOI:10.3389/fpubh.2026.1908891

Front Vet Sci. 2026 Aug 14;13:1912990. doi: 10.3389/fvets.2026.1912990. eCollection 2026.

ABSTRACT

BACKGROUND: Toxoplasma gondii is a major zoonotic pathogen causing reproductive losses in sheep and posing significant public health risks, particularly through meat consumption and congenital infection. Despite Afyonkarahisar Province being one of the most important sheep-producing regions in Türkiye, no farm-level seroepidemiological study with structured risk factor analysis had previously been conducted there.

METHODS: A cross-sectional study was conducted between September and December 2025 on 550 sheep blood samples collected from 55 commercial farms across Afyonkarahisar Province. Anti-T. gondii antibodies were detected using a commercial indirect ELISA (ID Screen^® Toxoplasmosis Indirect Multi-Species, IDvet), with samples classified as positive (sample-to-positive percentage [S/P%] ≥ 50%), doubtful (40%-50%), or negative (≤40%). A structured questionnaire was administered to collect 19 farm- and animal-level variables. Associations with seropositivity were evaluated by univariable analysis and a mixed-effects logistic regression model with farm as a random effect, with Firth’s penalized regression applied to obtain stable estimates where quasi-complete separation occurred.

RESULTS AND DISCUSSION: The overall animal-level seroprevalence was 42.2% (232/550; 95% CI: 38.0%-46.4%), and 44 of 55 farms (80.0%; 95% CI: 67.0%-89.6%) were classified as seropositive. In multivariable analysis using Firth’s penalized logistic regression, five variables were independently associated with higher seropositivity: flock-level history of abortion (aOR = 3.77; 95% CI: 2.41-6.00), age over 12 months (aOR = 3.54; 95% CI: 2.15-5.97), communal pasture use (aOR = 74.12; 95% CI: 10.22-9431.54, wide owing to quasi-complete separation), leaving aborted materials on site (aOR = 2.30; 95% CI: 1.49-3.61), and irregular barn cleaning (aOR = 2.32; 95% CI: 1.46-3.72). Cat presence was universal across all 55 farms, precluding statistical evaluation; however, stray cats had unrestricted access to feed and water on every farm, likely representing the primary driver of environmental oocyst contamination. Breed, sex, water source, and antiparasitic drug type were not significantly associated with seropositivity. T. gondii infection is highly endemic in sheep in Afyonkarahisar, with seroprevalence exceeding the national average. Stray cat access control, safe disposal of aborted materials, and routine differential diagnosis for abortifacient pathogens are recommended as priority interventions for reducing infection pressure and mitigating both animal health and public health risks within a One Health framework.

PMID:42666301 | PMC:PMC13521879 | DOI:10.3389/fvets.2026.1912990

Front Big Data. 2026 Aug 14;9:1811835. doi: 10.3389/fdata.2026.1811835. eCollection 2026.

ABSTRACT

Real-time data analysis plays an important role in the operation of digital urban systems, where the behavior of residents and the load on services can change over short periods of time. At the same time, traditional analytical approaches based on batch data processing often do not allow timely detection of such changes, which leads to delayed and not always accurate management decisions. This paper introduces an artificial intelligence-driven smart city system (AISSC) for real-time data trend analysis. The proposed AISSC framework processes streaming data in a smart city digital environment. The proposed approach encompasses real-time feature generation and statistical techniques for identifying significant changes. The proposed AISSC solution is executed on the Python platform. The results demonstrate that the proposed AISSC solution achieves a directional accuracy of 98.6% for trend prediction, together with strong numerical forecasting performance with a MAPE of 6.3% and a WMAPE of 7.8%. The framework detects statistically significant deviations within 2.4 s at the sliding-window level while maintaining an end-to-end system update cycle of approximately 5 min. These results demonstrate the capability of the proposed framework to support reliable real-time trend analysis and short-term forecasting for smart city decision-making. This shows that the framework can reliably identify trends and accurately estimate demand for real-time smart city decision-making. The results demonstrate consistent performance improvements compared to representative baseline methods under identical streaming and computational constraints. The proposed AISSC facilitates real-time observation of urban dynamics and enhances short-term forecasting accuracy for informed decision-making in smart city management systems.

PMID:42666299 | PMC:PMC13521872 | DOI:10.3389/fdata.2026.1811835

Front Microbiol. 2026 Aug 14;17:1902019. doi: 10.3389/fmicb.2026.1902019. eCollection 2026.

ABSTRACT

BACKGROUND: Type 2 diabetes (T2D) has been consistently associated with alterations in the gut microbiome, although disease, treatment, diet, and other host factors may contribute to the observed patterns. How these associations are organized across different biological levels of the microbial ecosystem remains incompletely understood.

METHODS: We performed shotgun metagenomic sequencing of fecal samples from 82 individuals, including 41 patients with T2D and 41 age-, sex-, and body mass index-matched healthy controls. Taxonomic profiling, functional pathway analysis, enterotype characterization, ecological network inference, and interpretable machine-learning approaches were integrated to characterize microbiome variation across multiple organizational levels.

RESULTS: Despite clear clinical differences between groups, particularly fasting blood glucose, the overall ecological architecture of the gut microbiome remained broadly preserved. Dominant phylum-level composition and enterotype structure were maintained, whereas variation became apparent at finer biological scales. Species-level analyses identified 42 differentially abundant taxa. Community diversity analysis showed reduced Chao1 richness (P = 0.024), increased Simpson diversity (P = 0.024), unchanged Shannon diversity (P = 0.126), and a modest shift in community composition (PERMANOVA, R ² = 0.040, P = 0.006). Functional profiling showed no pathway-level significance after multiple-testing correction but directional trends across several metabolic modules. Exploratory Spearman-based networks differed in topology between groups; because relative-abundance data are compositional, these differences cannot be interpreted as direct ecological interactions or definitive network rewiring. Machine-learning models achieved a within-cohort cross-validated AUC of up to 0.91, but lacked independent external validation.

CONCLUSIONS: These findings provide a multi-layer description of T2D-associated gut microbiome variation within this cohort. The data are consistent with preserved higher-order community organization accompanied by finer-scale differences in species composition, functional potential, community-state occupancy, statistical co-occurrence, and within-cohort discriminative features. Medication confounding, compositional effects, technical artifacts, and the absence of external validation limit causal, ecological, and diagnostic interpretation. Larger longitudinal, multi-site, medication-resolved, and independently validated studies are required.

PMID:42666298 | PMC:PMC13522148 | DOI:10.3389/fmicb.2026.1902019

Front Public Health. 2026 Aug 14;14:1858500. doi: 10.3389/fpubh.2026.1858500. eCollection 2026.

ABSTRACT

BACKGROUND: Civil Registration and Vital Statistics (CRVS) systems are fundamental to evidence-based governance and public health. In India, a persistent gender disparity exists in death registration: approximately 73% of male deaths are officially recorded compared to only 64% of female deaths nationally (NFHS-5). Gujarat, despite its relatively advanced socio-economic standing and near 93.1% overall death registration rate (CRS 2023), continues to exhibit this troubling gap.

OBJECTIVE: This study analyses the structural, economic, and socio-cultural drivers of gender disparities in death registration in Gujarat and proposes policy interventions aimed at achieving universal and gender-equitable registration completeness.

METHODS: This study employs a mixed-method policy analysis framework, synthesizing secondary data from the National Family Health Survey (NFHS-5), the Civil Registration System (CRS) 2023 Annual Report, Sample Registration System (SRS) data, and peer-reviewed literature. Qualitative insights are drawn from administrative case studies, district-level reports from Gujarat, and comparative analysis of high-performing states (Kerala and Tamil Nadu).

RESULTS: The gender gap in death registration was widest among the poorest wealth quintile (13 percentage points) and narrowed substantially among the richest quintile (4 percentage points). Key barriers included: (i) an economic-utility logic, whereby male deaths are prioritized due to implications for asset succession (“Varsai”); (ii) higher prevalence of female home deaths linked to healthcare access inequities; (iii) administrative and bureaucratic barriers at the Panchayat level; and (iv) under-reporting of socially sensitive female deaths, including maternal mortality and suicides.

CONCLUSION: Closing gender gaps in death registration requires a rights-based approach that integrates administrative simplification, strengthened community-level reporting through ASHA and Anganwadi networks, expanded digital infrastructure, and targeted public awareness initiatives. If equitably implemented, Gujarat’s digital governance architecture has the potential to substantially reduce female invisibility in official mortality statistics.

PMID:42666286 | PMC:PMC13522170 | DOI:10.3389/fpubh.2026.1858500

Front Psychiatry. 2026 Aug 14;17:1908580. doi: 10.3389/fpsyt.2026.1908580. eCollection 2026.

ABSTRACT

BACKGROUND: Exercise intervention has been associated with cognitive development in children. However, current study methods have not clarified the potential nonlinear association between exercise dosage and cognitive ability, and interpretable machine learning approaches may provide a novel perspective for exploring these complex relationships. Therefore, this study aimed to construct and verify a machine learning model of the relationship between exercise dosage and cognitive development in children.

METHODS: A total of 8623 valid samples from the China Family Panel Studies (CFPS) database were analyzed in this study. SPSS 25.0 was used to perform descriptive statistical analysis. SHAP values and partial dependence plots were used to enhance model interpretability. Three predictive models-Exercise Dose-Cognitive Ability Score (ED-CAS) model, Daily Physical Activity Duration-Cognitive Ability Score (DPAD-CAS) model, and Weekly Frequency of Physical Activity-Cognitive Ability Score (WFPA-CAS) model-were developed using the random forest algorithm.

RESULTS: The ED-CAS, DPAD-CAS, and WFPA-CAS models demonstrated moderate predictive performance (R² = 0.21, 0.14, and 0.11, respectively). SHAP analysis revealed mean marginal contributions of 0.12, 0.07, and 0.11 for ED, DPAD, and WFPA, respectively. Partial dependence analyses further identified normalized parameter peaks at 1.35 (ED), 1.4 (DPAD), and 0.9 (WFPA), indicating that these exercise-related features contributed differently to model predictions across dose ranges. However, dose thresholds were observed (≤720 minutes/week, ≤6 days/week, ≤85 minutes/day), beyond which CAS declined significantly.

CONCLUSIONS: This study identified a potential inverted U-shaped association between exercise dosage and cognitive ability in children. The observed dose ranges may provide preliminary reference information for future exercise intervention. However, longitudinal and experimental studies are required to determine causal relationships and establish evidence-based exercise recommendations.

PMID:42666282 | PMC:PMC13522174 | DOI:10.3389/fpsyt.2026.1908580

Math Financ Econ. 2026;20(2):405-453. doi: 10.1007/s11579-026-00418-5. Epub 2026 Aug 1.

ABSTRACT

We provide a stochastic analysis of an overlapping-generations model under incomplete markets. By casting individual optimization with idiosyncratic income risk into a forward-backward stochastic differential-equation (FBSDE) system, we (i) establish existence and uniqueness of the dynamic general-equilibrium interest rate and (ii) derive analytical and semi-explicit formulas for both the equilibrium interest-rate path and the natural borrowing limit – defined as the discounted expected shortfall of future income. Our FBSDE-based approach yields tractable policy functions and equilibrium mappings without relying on high-dimensional PDE methods, offering clear insights into how income dynamics and demographic structure drive interest-rate fluctuations and credit constraints.

PMID:42666272 | PMC:PMC13521973 | DOI:10.1007/s11579-026-00418-5