Category: Statistics

J Public Health Res. 2026 Feb 10;15(1):22799036251410258. doi: 10.1177/22799036251410258. eCollection 2026 Jan.

ABSTRACT

BACKGROUND: Over the past three decades, Iran’s fertility rate has declined sharply from 6.5 to 1.7, posing a critical demographic and public health challenge, a global trend that highlights the need to tackle multifaceted influences on childbearing intentions, including economic, social, emotional, and attitudinal factors.This study examined the factors influencing childbearing intentions among women.

DESIGN AND METHODS: This cross-sectional study surveyed 450 reproductive-age women in Tabriz, Iran. Data were collected using self-administered questionnaires to assess sociodemographic/obstetric characteristics, attitudes toward fertility/childbearing, subjective norms, marital satisfaction, perceived social support, childbearing/parental anxiety, and hope. Data were analyzed with SPSS v24 via descriptive statistics, chi-square/Fisher’s exact tests, independent t-tests, and hierarchical multiple logistic regression to identify predictors of childbearing intention.

RESULTS: Only 34.2% (95% CI: 29.8-38.8) of participants intended to have children. Adjusted logistic regression identified positive associations with childbearing intention for positive attitudes (OR = 1.113, 95% CI: 1.057-1.172), subjective norms (OR = 1.458, 95% CI: 1.292-1.646), social support (OR = 1.093, 95% CI: 1.020-1.172), hope (OR = 1.165, 95% CI: 1.043-1.172), and religious beliefs (OR = 12.789, 95% CI: 1.029-158.990); conversely, negative associations for pregnancy/childbirth anxiety (OR = 0.633, 95% CI: 0.422-0.949), age > 40 years (OR = 0.01, 95% CI: 0.000-0.279), and poor financial status (OR = 0.007, 95% CI: 0.000-0.347).

CONCLUSION: The findings highlight the multifaceted economic, social, emotional, and attitudinal influences on childbearing intentions among Iranian women. To promote fertility rates, targeted public health strategies are recommended, including counseling for emotional barriers, economic supports like infertility subsidies and family incentives, and community-based education on reproductive health benefits.

PMID:41685375 | PMC:PMC12891384 | DOI:10.1177/22799036251410258

Front Neurosci. 2026 Jan 28;20:1766192. doi: 10.3389/fnins.2026.1766192. eCollection 2026.

ABSTRACT

INTRODUCTION: Disruptions in functional connectivity (FC) within the default mode network (DMN) are well established as a key neuropathology underlying cognitive impairment in type 2 diabetes mellitus (T2DM). Subcortical nuclei, including the basal forebrain (BF) and mediodorsal thalamus, play critical roles in regulating DMN-associated cognitive processes and are particularly vulnerable to hyperglycemia and brain insulin resistance. However, the specific FC patterns between these subcortical nuclei and DMN cortical regions in patients with T2DM, as well as their potential associations with cognitive impairment, remain incompletely elucidated.

METHODS: Eighty-two patients with T2DM and 79 healthy controls (HCs) were enrolled in this study. Clinical data, neuropsychological assessments, and resting-state functional magnetic resonance imaging were collected from all participants. Resting-state (rs-FNC) and dynamic (dFNC) functional network connectivity analyses were performed to characterize connectivity between subcortical nuclei and DMN cortical regions. Correlation analyses explored associations between FNC metrics showing significant intergroup differences and participants’ clinical and cognitive parameters.

RESULTS: rs-FNC analysis revealed decreased FC between the BF and the dorsomedial prefrontal cortex (dMPFC), the BF and the temporal pole, and the dMPFC and the anteromedial prefrontal cortex in patients with T2DM (network-based statistic correction; edge p < 0.001, component p < 0.05). dFNC analyses indicated increased frequency and prolonged mean dwell time (MDT) of State 1 (high-frequency low-connectivity), as well as decreased frequency and shortened MDT of State 2 (high-frequency high-connectivity) compared with HCs (all p < 0.05). Reduced FC between the dMPFC and BF was positively correlated with Montreal Cognitive Assessment scores (r = 0.353, p = 0.001), whereas frequency (r = -0.434, p < 0.001) and MDT (r = -0.376, p = 0.001) of State 2 were negatively correlated with T2DM disease duration after Bonferroni correction.

CONCLUSION: These findings indicate that T2DM duration correlates with reduced highly efficient DMN connectivity, and that the BF may regulate cognitive function via the dMPFC subsystem. The results reveal temporal and functional specificity in abnormal DMN connectivity in patients with T2DM and enrich the neural atlas of DMN dysfunction in this population.

PMID:41685355 | PMC:PMC12891212 | DOI:10.3389/fnins.2026.1766192

J Arrhythm. 2026 Feb 10;42(1):e70285. doi: 10.1002/joa3.70285. eCollection 2026 Feb.

ABSTRACT

BACKGROUND: It remains unclear how P-wave morphology characteristics can be used to stratify the risk of late recurrence after catheter ablation (CA) for atrial fibrillation (AF).

METHODS: Patients with paroxysmal AF who underwent an initial CA were enrolled. We investigated the association between P-wave morphology (P-wave duration (Pd), PQ interval, P-wave amplitude (PWA) in leads II, V2, and V6) and late arrhythmia recurrence. Patients were classified into groups using statistical methods, and differences in recurrence and predictive scores for low voltage areas (LVA) among the groups were evaluated.

RESULTS: A total of 1005 paroxysmal AF patients undergoing initial CA were included. Cox regression identified female sex, Pd > 124 ms, PQ > 196 ms, and low PWA in leads II, V2, and V6 as predictors of late recurrence. Hierarchical clustering defined three phenotypes: Phenotype 1 (isolated low PWA), Phenotype 2 (isolated prolonged Pd) and Phenotype 3 (low PWA with prolonged Pd). At 1-year, cumulative recurrence rates were 10.1% (95% CI 0.8-15.7), 7.0% (4.7-9.6), and 36.2% (30.8-42.3) for Phenotypes 1-3; at 3-year, rates were 17.4% (12.8-23.3), 10.2% (7.4-14.0), and 61.2% (54.8-67.6). Phenotype 3 showed the highest risk, with HRs of 4.84 (95% CI 3.42-6.84) versus Phenotype 1 and 7.44 (4.34-12.8) versus Phenotype 2 (both p < 0.001). Phenotype 3 also had higher DR-FLASH and APPLE scores than the other phenotypes.

CONCLUSIONS: Low PWA across multiple leads (II, V2, and V6), especially when combined with prolonged Pd, correlates with late arrhythmia recurrence and suggests the potential presence of LVA.

PMID:41685353 | PMC:PMC12891814 | DOI:10.1002/joa3.70285

NAR Genom Bioinform. 2026 Feb 11;8(1):lqag012. doi: 10.1093/nargab/lqag012. eCollection 2026 Mar.

ABSTRACT

Synthetic data (SD) has become an increasingly important asset in the life sciences, helping address data scarcity, privacy concerns, and barriers to data access. Creating artificial datasets that mirror the characteristics of real data allows researchers to develop and validate computational methods in controlled environments. Despite its promise, the adoption of SD in life sciences hinges on rigorous evaluation metrics designed to assess their fidelity and reliability. To explore the current landscape of SD evaluation metrics in distinct life sciences domains, the ELIXIR Machine Learning Focus Group performed a systematic review of the scientific literature following the PRISMA guidelines. Six critical domains were examined to identify current practices for assessing SD. Findings reveal that, while generation methods are rapidly evolving, systematic evaluation is often overlooked, limiting researchers’ ability to compare, validate, and trust synthetic datasets across different domains. This systematic review underscores the urgent need for robust, standardized evaluation approaches that not only bolster confidence in SD but also guide its effective and responsible implementation. By laying the groundwork for establishing domain-specific yet interoperable standards, this scoping review paves the way for future initiatives aimed at enhancing the role of SD in scientific discovery, clinical practice and beyond.

PMID:41685350 | PMC:PMC12891913 | DOI:10.1093/nargab/lqag012

Front Genet. 2026 Jan 29;17:1729712. doi: 10.3389/fgene.2026.1729712. eCollection 2026.

ABSTRACT

OBJECTIVES: Hyperuricemia and gout are common public health problems, stemming from both genetic and lifestyle factors. Evidence from multi-ethnic regions in Yunnan Province remains limited. This preliminary study examined hyperuricemia and gout prevalence, related biomarkers, lifestyle patterns, and SLC2A9/SLC22A12 genetics variations among 88 participants from the Miao community in Yunnan Province China.

METHODS: A cross-sectional survey and biochemical study were conducted. Demographic and lifestyle data were collected, and blood samples were analyzed for serum biochemical indicators. Eight SNPs in SLC2A9 and SLC22A12 were genotyped. Logistic regression models were applied to allele and genotype data.

RESULTS: Demographic and clinical analyses for Miao villagers (n = 88) suggested that the morbidities of hyperuricemia and gout were more frequent in male and showed significant association with alcohol consumption, smoking, and elevated BMI. While dietary patterns showed no significant differences. Compared with non-hyperuricemia/non-gout individuals (n = 56), the hyperuricemia/gout group (n = 57) showed 56% higher uric acid (553.13 vs. 354.73 μmol/L), 37% elevated creatinine (84.66 vs. 61.80 μmol/L), and higher triglycerides (3.35 vs. 1.80 mmol/L), along with hematological abnormalities, e.g., elevated hemoglobin (162.77 vs. 147.50 g/L) and lower platelets counts (161.09 vs. 194.14 × 10⁹/L). Preliminary genetic analyses indicated a possible association between SLC2A9_rs10939650 and hyperuricemia/gout risk, whereas variant SLC22A12 polymorphisms showed no association. After Bonferroni correction, no SNPs remained statistically significant.

CONCLUSION: This preliminary study suggested that the relatively higher burden of hyperuricemia and gout in the Miao population may be influenced by ethnicity, sex, lifestyle factors, metabolic alteration, and potential genetic components. Given the small sample size, the genetic findings should be interpreted cautiously and validated in larger studies for that disease (hyperuricemia and gout) and for similar ethnic community.

PMID:41685348 | PMC:PMC12893670 | DOI:10.3389/fgene.2026.1729712

Shoulder Elbow. 2026 Feb 10:17585732261419033. doi: 10.1177/17585732261419033. Online ahead of print.

ABSTRACT

BACKGROUND: This study aimed to evaluate recovery of complex upper-limb movements from a kinematic and biomechanical perspective in patients undergoing Reverse Total Shoulder Arthroplasty (RSA), comparing movement quality during athletic gestures with healthy controls.

METHODS: Two groups were analyzed: patients with RSA and healthy individuals without shoulder pathology. Participants performed basic shoulder tasks (flexion-extension and abduction-adduction) and three athletic gestures of increasing complexity: boccia throw, golf swing, and padel víbora stroke. Kinematic data (joint angles, angular velocities, and accelerations) were collected using a wearable inertial motion analysis system (Movit System G1).

RESULTS: Controls demonstrated a greater range of motion (maximum joint angle: 184.0° vs. 144.03°), though differences were not statistically significant. Angular velocities and accelerations were largely comparable between groups, indicating that patients with RSA adopt conservative yet functional movement strategies. No significant differences were observed during the boccia throw or golf swing. The víbora stroke showed the highest variability but remained within functional limits in both groups.

CONCLUSIONS: This pilot feasibility study suggests that patients with RSA can perform complex upper-limb and sport-specific movements with biomechanical patterns comparable to healthy individuals. Although limited by small sample size, large effect sizes indicate clinically relevant differences, supporting the need for larger, confirmatory studies.

PMID:41685344 | PMC:PMC12890591 | DOI:10.1177/17585732261419033

J Forensic Leg Med. 2026 Feb 10;118:103088. doi: 10.1016/j.jflm.2026.103088. Online ahead of print.

ABSTRACT

INTRODUCTION: Ketoacidosis is a form of metabolic acidosis caused by the excess production of ketone bodies. It can be commonly found in the context of both diabetes mellitus and alcohol dependency but is also associated with a myriad other aetiologies. To date the extent of risk of developing ketoacidosis is unclear in diabetic persons who are alcohol dependent and/or have abused alcohol acutely as in ‘binge drinking’.

METHODOLOGY: We performed a retrospective analysis of consecutive coroners’ autopsies between 2015 and 2023 in a London Coroner’s jurisdiction of individuals aged 18 years and above to assess whether significant ketoacidosis, when present, was of diabetic or alcoholic aetiology or a combination of both. Data was obtained from the medical history, circumstances of death, histology, toxicology and biochemical markers. The deceased individuals were surveyed and categorised into the following three groups: 1. Individuals with diabetes mellitus type 1or 2 and with no known history of alcohol dependency according to their medical history; 2. Alcohol dependent persons or persons abusing alcohol acutely, without diabetes mellitus; 3. Diabetic individuals with known alcohol dependency or acute abuse as in ‘binge drinking’. Individuals suffering from other causes of ketoacidosis were excluded.

RESULTS: From an overall total of 3873 autopsies performed of persons 18 years or above over a 9-year period (2015-2023), 1021 cases were analysed and divided into three groups as stated above. Group 1 consisted of 635 diabetic individuals, with ketoacidosis present in 23 (3.6%). Group 2 consisted of 333 individuals with alcohol dependency, in which ketoacidosis was present in 17 (5.1%). Group 3 consisted of 56 individuals, with both diabetes and alcohol dependency, in which ketoacidosis was present in 7 (13%).

CONCLUSIONS: This study demonstrated a statistically significant risk of developing ketoacidosis in all individuals with both diabetes mellitus and alcohol dependency (Group 3) when compared to diabetics alone (Group 1): Risk ratio = 3.8; p = .0001). There was less but significant increased risk when females alone were compared in these two groups. Less but significant increased risk was also found in all Group 3 individuals when compared to those in the alcohol alone category (Group 2) or when all individuals or males alone were compared between Group 1 + Group 2 with those in (Group 3). There was no significant increased risk when diabetics in Group 1 were compared to persons with alcohol dependency in Group 2.

PMID:41678866 | DOI:10.1016/j.jflm.2026.103088

Chemosphere. 2026 Feb 11;396:144856. doi: 10.1016/j.chemosphere.2026.144856. Online ahead of print.

ABSTRACT

Atrazine is one of the most used herbicides in Argentina. This stable and persistent compound was detected in the environment, even exceeding permitted concentration limits. In this sense, the present work focuses on selecting a defined actinomycetota consortium with atrazine removal abilities, determining the phytotoxicity of the liquid-treated systems, and identifying genes involved in the herbicide catabolism. For that, four actinomycetota consortia (C1, C2, C3, and C4) were tested about their ability to grow and remove 25 and 50 mg L^-1 of atrazine as the only carbon source. The best growth and removal efficiency were detected for C1, constituted by Streptomyces sp. A2, A5, A11, and M7. This consortium was selected and tested on their ability to use atrazine as a sole nitrogen source, and no statistically significant differences (p > 0.05) were observed between the growth values detected with atrazine as a carbon (2.98 ± 0.13 g L^-1) or nitrogen source (2.88 ± 0.18 g L^-1). However, a removal decrease of 13.3% was observed with the herbicide as a nitrogen source. Phytotoxicity tests demonstrated the ability of C1 to reverse the herbicide toxicity, especially with atrazine as a carbon source. Moreover, the presence of at least one of the genes that encode enzymes involved in the herbicide degradation was detected in all C1 members. These results demonstrated the ability of C1 to remove atrazine and use it as a carbon or nitrogen source, revealing their metabolic versatility and potential cooperative work, fundamental for the degradation of xenobiotic compounds.

PMID:41678860 | DOI:10.1016/j.chemosphere.2026.144856

Spectrochim Acta A Mol Biomol Spectrosc. 2026 Feb 8;353:127560. doi: 10.1016/j.saa.2026.127560. Online ahead of print.

ABSTRACT

Construction and demolition waste (C&DW) accounts for nearly one-third of total waste generation in the European Union, representing a significant environmental challenge. Although recovery rates are high (∼89%), much of the recycled material is downcycled, hindering true circular economy goals. This study proposes an integrated analytical method combining portable X-ray fluorescence (XRF), near-infrared hyperspectral imaging (NIR-HSI), and Shallow Neural Networks (SNN) for fast, accurate classification of earthquake-related C&DW from central Italy. Thirty sample sets from the 2016-2017 earthquake zones in Abruzzo, Marche, and Emilia Romagna were analyzed using portable energy-dispersive XRF to define three recycling-oriented material classes: concrete-based (CON), ceramic-rich (CER), and natural aggregates (NAT). Statistical tests and principal component analysis (PCA) confirmed significant differences among classes. NIR-HSI spectra (1000-1700 nm) were processed to train an SNN with a single hidden layer. The classifier showed excellent precision, recall, specificity, and F1-scores (≥ 0.98) across classes, with misclassifications limited to borderline cases like glazed ceramics. The goal of this work is to evaluate the best achievable performance within a controlled feasibility framework, demonstrating that the coupling of NIR-HSI with SNN provides a rapid, robust, and transferable strategy for automated C&DW classification, thereby supporting circular economy goals through improved material recovery and recycling efficiency.

PMID:41678854 | DOI:10.1016/j.saa.2026.127560

J Chem Theory Comput. 2026 Feb 12. doi: 10.1021/acs.jctc.6c00005. Online ahead of print.

ABSTRACT

We present a comprehensive benchmark of excited-state polarizabilities for a representative set of more than 40 singlet states from 27 small organic molecules. Reference data were obtained using the high-level coupled-cluster CC3 model in combination with the aug-cc-pVTZ atomic basis set, providing the first systematic data set of excited-state polarizabilities at this level of theory. The studied set includes both valence and Rydberg states, the latter exhibiting significantly larger polarizabilities, reflecting their diffuse character and enhanced sensitivity to external electric fields. The benchmark analysis includes lower-level wave function-based methods, namely, CCSD and CC2, as well as Time-Dependent Density Functional Theory (TD-DFT) with several common density functional approximations (B3LYP, MN15, M06-2X, CAM-B3LYP, and LC-BLYP). The statistical analysis enables the evaluation of the impact of orbital relaxation and highlights method-dependent differences across the different kinds of excited states. The results indicate that CCSD, in both its relaxed and unrelaxed forms, provides the most accurate description of excited-state polarizabilities, closely followed by CC2, which can therefore be generally employed as a computationally efficient yet reliable alternative. Among the TD-DFT functionals, range-separated hybrids─particularly LC-BLYP─perform best, while larger errors are observed for the three evaluated global hybrids.

PMID:41678842 | DOI:10.1021/acs.jctc.6c00005