Category: Statistics

BMJ Public Health. 2026 Aug 5;4(3):e005074. doi: 10.1136/bmjph-2026-005074. eCollection 2026.

ABSTRACT

INTRODUCTION: Peer-to-peer HIV self-testing (HIVST) has shown promise in addressing barriers to HIV testing challenges by leveraging social networks and peer influence to promote health-seeking behaviours.

OBJECTIVE: To explore the perceived feasibility and acceptability of the peer-to-peer HIVST distribution model among adolescents and young people aged 15-24 years in Uganda.

METHODS: We conducted a descriptive exploratory qualitative study in Wakiso District, Uganda. Data were collected through six focus group discussions (n=68) and 14 in-depth interviews, including interviews with peer leaders. Participants were purposively recruited through community meetings with support from Village Health Teams. Discussions explored perceptions of peer-to-peer HIVST distribution, including potential barriers and facilitators. Interviews were audio-recorded, transcribed verbatim, translated into English and analysed using thematic analysis.

RESULTS: Participants perceived the peer-to-peer HIVST distribution model as both feasible and acceptable. Key facilitators of feasibility included peer trust, structured training, community-based delivery and integration with existing health structures. Perceived barriers included logistical constraints, inadequate supervision, kit storage challenges and concerns about equitable reach. Acceptability was driven by trust, confidentiality, emotional support, autonomy and the relatability of peer distributors. However, concerns about gossip, stigma, confidentiality breaches and the emotional burden placed on peer distributors were identified as potential barriers to sustained acceptability.

CONCLUSION: Peer-to-peer HIVST distribution was perceived as a feasible and acceptable approach for increasing HIV testing among adolescents and young people. Future implementation efforts should strengthen peer training and supervision, address confidentiality and stigma concerns, provide psychosocial support for peer distributors, and ensure equitable access for socially marginalised adolescents.

PMID:42569013 | PMC:PMC13448566 | DOI:10.1136/bmjph-2026-005074

ACS Omega. 2026 Jul 22;11(30):44614-44633. doi: 10.1021/acsomega.5c10279. eCollection 2026 Aug 4.

ABSTRACT

This study presents an in-depth examination of the swelling characteristics of biopolymeric hydrogels developed with sodium alginate, employing both conventional and modern modeling techniques to predict and optimize the process. Hydrogel swelling properties have found critical applications in controlled drug delivery, wound dressing, and food technology applications, and thus have developed a high demand for predictive and tuning strategies. In this case, different concentrations of polymers, cross-linkers, microalgal cells, and media volume are set with different compositional parameters. The measurements of experimental swelling degrees were conducted under controlled conditions to obtain both equilibrium and dynamic measurements. Initial data analysis was performed by response surface methodology (RSM) with a central composite design (CCD), which explained the effects of independent and interactive formulation factors. Then, an artificial neural network (ANN) model was implemented and trained on the same data set to elicit possible complex and nonlinear associations that are not considered in traditional approaches. The results of the two models were evaluated intensively based on the statistical parameters such as R², RMSE, and the analysis of the residuals. The ANN model appeared more predictive and produced finer nonlinear trends in the swelling response when compared to RSM, which generated understandable equations and response surfaces required to develop mechanistic insight. It is found that the use of hybrid modeling is one of the possible future directions because the complementary strengths were evaluated in terms of comparative analysis. The results show that machine learning and statistical design are synergistic in the study and optimization of hydrogel systems. The article develops the methodological toolkit that can be used to study hydrogels as well as establishes a basis for intelligent material design with data-centric design, which is more likely to be practical with better functionality and performance.

PMID:42569012 | PMC:PMC13448944 | DOI:10.1021/acsomega.5c10279

Geohealth. 2026 Aug 7;10(8):e2025GH001699. doi: 10.1029/2025GH001699. eCollection 2026 Aug.

ABSTRACT

The intensification of extreme heat events in the Mediterranean basin poses growing threats to public health, particularly in climate-vulnerable regions like the Valencian Region (eastern Spain). Despite the implementation of provincial and municipal heat prevention plans, their efficacy remains unevaluated, and most studies have focused on provincial capitals, potentially overlooking subregional variability. This study addresses these gaps by quantifying moderate and extreme heat-attributable mortality across 28 thermoclimatic areas (TAs)-a climatic subdivision of the Valencian Region- from 1975 to 2019, using a two-stage time-series analysis of high-resolution temperature and mortality data. Results reveal a distinct coastal-inland gradient, with significantly higher mortality impacts in inland TAs compared to coastal provincial capitals. Areas most impacted by extreme heat are concentrated in interior regions, while coastal capitals exhibit lower risks. These findings underscore the limitations of relying on administrative boundaries for public health surveillance and adaptation planning. The study highlights the value of climatically coherent zones, such as TAs, for improving the spatial resolution of early warning systems and tailoring heat prevention strategies. This scalable methodological framework provides critical insights for enhancing the design of heat adaptation plans not only in Spain but also in other Mediterranean and climate-sensitive regions.

PMID:42569010 | PMC:PMC13449177 | DOI:10.1029/2025GH001699

Int J Dent. 2026 Aug 7;2026:3153277. doi: 10.1155/ijod/3153277. eCollection 2026.

ABSTRACT

BACKGROUND: Periodontitis is a prevalent inflammatory disease affecting the supporting structures of the teeth and has been strongly associated with systemic conditions such as diabetes mellitus. Poor glycemic control has been reported to exacerbate periodontal tissue destruction; however, evidence from many developing countries remains limited. This study aimed to evaluate the association between glycemic parameters and periodontitis severity in a hospital-based population in Nepal.

METHODS: A hospital-based cross-sectional study was conducted among 396 adult patients attending the dental outpatient department of a tertiary care hospital in Nepal. Participants were categorized according to the severity into mild (n = 132), moderate (n = 132), and severe (n = 132) groups based on periodontal clinical examination. The terminology was aligned with the 2017 World Workshop classification of periodontal and peri-implant diseases and conditions. Full periodontal grading was not assigned because longitudinal data on disease progression were unavailable. Patients presenting with a molar-incisor pattern suggestive of the previously described aggressive periodontitis phenotype were excluded. Demographic variables, smoking status, periodontal clinical parameters, and glycemic indicators, including fasting blood glucose (FBG), postprandial blood sugar (PPBS), and glycated hemoglobin (HbA1c), were recorded. Descriptive statistics were used to summarize the study variables. Differences in glycemic parameters across periodontitis severity groups were assessed using the Kruskal-Wallis test. Spearman correlation analysis was applied to assess the association between glycemic markers and periodontal clinical parameters. Ordinal logistic regression was conducted to determine the independent predictors of increasing severity of periodontitis.

RESULTS: Glycemic parameters worsened with increasing severity of periodontitis. Patients with severe periodontitis had markedly increased levels of FBG, PPBS, and HbA1c in comparison to those with mild and moderate periodontitis (p < 0.001). Periodontal clinical parameters, such as probing depth and clinical attachment loss (CAL), were most strongly correlated with HbA1c (p < 0.001). Ordinal logistic regression analysis revealed that HbA1c was the most significant independent predictor of increasing severity of periodontitis, followed by age and current smoking status.

CONCLUSIONS: Severe periodontitis was significantly associated with worsening glycemic status. Of all the assessed glycemic markers, HbA1c exhibited the most robust relationship with periodontal destruction. These findings highlight the importance of glycemic control in periodontal health and support the need for integrated medical-dental management strategies for patients with metabolic disorders.

PMID:42569004 | PMC:PMC13449026 | DOI:10.1155/ijod/3153277

Front Med (Lausanne). 2026 Jul 24;13:1871693. doi: 10.3389/fmed.2026.1871693. eCollection 2026.

ABSTRACT

BACKGROUND: Patients with coexisting type 2 diabetes mellitus (T2DM) and hypertension (HTN) face a synergistically elevated risk of major adverse cardiovascular events (MACE). Evidence for prediction models developed specifically in established T2DM-HTN comorbidity population remains limited.

OBJECTIVE: To methodologically explore and preliminarily evaluate an interpretable machine learning framework for 1-year MACE prediction in hospitalized patients with coexisting T2DM and HTN using routine clinical data.

METHODS: This retrospective study included 1,054 hospitalized patients with T2DM and HTN, of whom 249 (23.6%) experienced MACE during 1-year follow-up. The dataset was randomly divided into training (60%), validation (20%), and independent test (20%) cohorts using stratified sampling. LASSO regression was applied for feature selection from 69 clinical variables. Four algorithms, including logistic regression, random forest, support vector machine, and XGBoost, were developed and compared. Model performance was assessed using discrimination, calibration, and clinical utility metrics. SHapley Additive exPlanations (SHAP) were used to interpret the final model.

RESULTS: LASSO identified six stable predictors: HbA1c, age, hypertension duration, cystatin C (CysC), T2DM duration, and carotid intima-media thickness (CIMT). Sex was additionally incorporated based on clinical relevance. Multivariable logistic regression showed that HbA1c, age, hypertension duration, T2DM duration, CysC, and CIMT were associated with 1-year MACE risk, whereas sex was not statistically significant. Logistic regression showed the best relative balance between discrimination, calibration, and simplicity on the validation set, although learning curves indicated limited incremental improvement with increasing training sample size. After isotonic regression recalibration, the final logistic regression model achieved an ROC-AUC of 0.828, a PR-AUC of 0.656, and a Brier score of 0.116 on the independent test set. Decision curve analysis indicated potential clinical net benefit. SHAP linked model predictions to glycemic burden, aging, cumulative disease exposure, renal-related risk, and subclinical atherosclerosis.

CONCLUSION: An interpretable logistic regression model based on seven routine clinical variables showed relatively good internal performance for predicting 1-year composite MACE risk in hospitalized patients with coexisting T2DM and HTN. CysC provided additional prognostic information beyond its conventional role as a renal filtration marker, although this association should be interpreted as prognostic rather than causal. External validation is required before the model can be considered for clinical decision support.

PMID:42568987 | PMC:PMC13448788 | DOI:10.3389/fmed.2026.1871693

Front Med (Lausanne). 2026 Jul 24;13:1786718. doi: 10.3389/fmed.2026.1786718. eCollection 2026.

ABSTRACT

OBJECTIVE: To systematically evaluate the efficacy of orthokeratology combined with atropine versus orthokeratology alone in treating myopia in children.

METHODS: Randomized controlled trials (RCTs) comparing the efficacy of orthokeratology combined with atropine versus orthokeratology alone for pediatric myopia were retrieved from databases including CNKI, Wanfang, VIP, CBM, PubMed, Cochrane Library, Embase, and Web of Science from inception to April 2025. Data were analyzed using RevMan 5.2 software.

RESULTS: A total of 18 randomized controlled trials involving 1,669 myopic children were included. The analysis showed that the intervention group had greater improvements in axial elongation (SMD = -0.66, 95% CI = -0.80 to -0.53, p < 0.001), tear film break-up time (SMD = 0.48, 95% CI = 0.33 to 0.63, p < 0.001), and corneal curvature (SMD = -2.47, 95% CI = -4.21 to -0.73, p = 0.005) compared to the control group. However, no statistically significant differences were found between the two groups in uncorrected visual acuity (SMD = 0.49, 95% CI = -0.27 to 1.24, p = 0.21) or tear film lipid layer thickness (SMD = -0.00, 95% CI = -1.09 to 1.09, p = 1.00). In addition, increased pupil diameter (SMD = 0.37, 95% CI = 0.09 to 0.64, p < 0.001) and reduced accommodative amplitude (SMD = -1.50, 95% CI = -2.58 to -0.43, p = 0.006) reflected the side effects associated with combined atropine treatment.

CONCLUSION: Compared with orthokeratology alone, orthokeratology combined with atropine treatment reduces axial elongation, tear film break-up time, and corneal curvature in myopic children, but shows no significant advantage in uncorrected visual acuity or tear film lipid layer thickness, while incurring side effects of increased pupil diameter and reduced accommodative amplitude.

PMID:42568973 | PMC:PMC13448785 | DOI:10.3389/fmed.2026.1786718

AJOG Glob Rep. 2026 Jul 10;6(3):100673. doi: 10.1016/j.xagr.2026.100673. eCollection 2026 Aug.

ABSTRACT

OBJECTIVE: To determine whether higher-dose aspirin (150-162 mg/d) reduces preeclampsia risk compared with lower-dose aspirin (75-81 mg/d) in pregnant women at elevated risk, using pooled evidence from all available head-to-head randomized controlled trials.

DATA SOURCES: PubMed/MEDLINE, Cochrane CENTRAL, Embase, Scopus, and ClinicalTrials.gov were searched from inception through April 27, 2026.

STUDY ELIGIBILITY CRITERIA: Parallel-group randomized controlled trials comparing at least two aspirin dose arms (head-to-head dose comparison) in pregnant women at elevated risk for preeclampsia, with a binary preeclampsia outcome reported. Aspirin-vs-placebo trials were excluded.

STUDY APPRAISAL AND SYNTHESIS METHODS: Log odds ratios were pooled using restricted maximum likelihood (REML) estimation with the Hartung-Knapp-Sidik-Jonkman (HKSJ) correction. Risk of bias was assessed using the Cochrane RoB 2 tool; evidence certainty was graded using GRADE. Egger’s test, Duval-Tweedie trim-and-fill, and univariate meta-regression (geography, dose ratio, gestational age at initiation) were performed.

RESULTS: Six randomized controlled trials enrolling 1099 participants across five countries were included. REML+HKSJ pooled OR 1.93 (95% CI 0.84-4.42, P=.096; I²=64.9%), representing approximately 48% lower odds of preeclampsia with higher-dose aspirin, a clinically substantial effect size that did not reach conventional statistical significance, primarily due to limited sample size (N=1099) and substantial between-study heterogeneity. Egger’s test was significant (P=.010); trim-and-fill estimated three missing studies (adjusted OR 1.92, 95% CI 1.47-2.50). No significant dose advantage was seen in North American trials (OR 1.25, 95% CI 0.67-2.34). A safety signal for placental abruption was identified with higher-dose aspirin in one large trial (8 vs 0 events). GRADE certainty: Very Low.

CONCLUSION: Applying conservative statistical methods (REML+HKSJ), higher-dose aspirin (150-162 mg/d) was associated with approximately 48% lower odds of preeclampsia vs lower-dose aspirin (75-81 mg/d; OR 1.93), a clinically meaningful effect that did not reach conventional statistical significance (95% CI 0.84-4.42, P=.096) due to limited sample size and heterogeneity. Clinical significance and statistical significance must be considered independently; the magnitude of this effect warrants serious attention in guideline discussions. A placental abruption safety signal warrants further investigation. Larger, harmonized head-to-head trials with preterm preeclampsia as the primary endpoint are needed.

PMID:42568969 | PMC:PMC13448443 | DOI:10.1016/j.xagr.2026.100673

ACS Omega. 2026 Jul 17;11(30):44761-44774. doi: 10.1021/acsomega.6c01167. eCollection 2026 Aug 4.

ABSTRACT

Understanding the electronic structure of amino acids is crucial to understanding protein stability, folding mechanisms, and molecular interactions. In this study, we introduce fragment-wise mutual information (FMI) as a quantum information-based tool to quantify interatomic correlations in peptides. By extending mutual information (MI) analysis to amino acid fragments, FMI provides a detailed map of electronic interactions beyond classical descriptors, such as van der Waals forces. We first validated FMI on 400 dipeptides, demonstrating a correlation with the atomization and bonding energies. Expanding this approach to the 10-mer Neh2 peptide, we analyze molecular dynamics (MD) simulations and reveal how interatomic correlations evolve during folding. Our results show that FMI distinguishes stabilizing interactions such as salt bridges and variable hydrogen-bond strengths, providing deeper insight into peptide stability. These findings suggest that FMI could enhance molecular modeling and force-field development by incorporating quantum electronic effects into biomolecular analysis.

PMID:42568960 | PMC:PMC13448925 | DOI:10.1021/acsomega.6c01167

J Nutr Metab. 2026 Aug 6;2026:5114961. doi: 10.1155/jnme/5114961. eCollection 2026.

ABSTRACT

INTRODUCTION: Anemia is one of the most widespread diseases, with one in four people affected by anemia worldwide. In sub-Saharan Africa, anemia in preschool children is considered a severe public health problem. This study aimed to assess the prevalence of anemia and its associated factors among 6-59-month-old children in Ayder Comprehensive Specialized Referral Hospital, Tigray, Northern Ethiopia.

METHODS: A hospital-based cross-sectional study was conducted among systematically selected 423 6-59-month-old children who were seeking service at Ayder Comprehensive Specialized Referral Hospital. Data were collected using a structured questionnaire. Four mL of venous blood from the finger was collected and analyzed using a Sysmex machine (model XP-300). Anemia in children was defined as a hemoglobin level below 11 g/dL. Data were entered and analyzed using SPSS Version 21. Variables with a p value of < 0.2 in the bivariable analysis were selected for multivariable logistic regression, and statistical significance was declared at p value < 0.05 and CI of 95%.

RESULTS: The prevalence of anemia among children aged 6-59 months was 57.1% (95% confidence interval: 52.2%-62.1%); of this magnitude, mild, moderate, and severe anemia was 27.1%, 20.9%, and 9.1%, respectively. Morphological, microcytic hypochromic anemia was the most common type of anemia. Children aged 6-23 months (adjusted odds ratio = 2.374; 95% confidence interval: 1.428-3.945), stunting (adjusted odds ratio = 2.543; 95% confidence interval: 1.503-4.302), underweight (adjusted odds ratio = 6.660; 95% confidence interval: 3.046-14.566), and intestinal parasite infection (adjusted odds ratio = 2.803; 95% confidence interval: 1.242-6.322) were factors associated with anemia.

CONCLUSION: The prevalence of anemia shows that it is a severe public health problem. Our findings underscore the need for nutrition counseling, deworming, growth monitoring, and promotion to minimize stunting, underweight, and intestinal parasite infection among children.

PMID:42568935 | PMC:PMC13448154 | DOI:10.1155/jnme/5114961

BMJ Public Health. 2026 Aug 5;4(3):e005035. doi: 10.1136/bmjph-2026-005035. eCollection 2026.

ABSTRACT

BACKGROUND: Using vital historical data, we modelled tuberculosis (TB) incidence and mortality rates across different scenarios of United States government’s (US) development assistance for health (DAH), domestic general government health spending (GHES) and non-US donor funding to determine how changes in these funding would affect TB incidence and mortality in Africa.

METHODS: A serial cross-sectional ecological analysis was conducted using a panel dataset covering the period from 1990 to 2022 for all 54 African countries. The dataset included age-standardised TB incidence and mortality rates, source-specific DAH and other socioeconomic variables. Mixed-effects tests were performed to assess associations among US DAH, other healthcare funding and TB outcomes.

RESULTS: Total annual TB-specific DAH in Africa increased from US$4.4 million in 1990 to US$168.7 million in 2022. The US government contributed more than a quarter of the total funds (US$713 million; 27.4%). Compared with scenarios in which US DAH was low but other funds were high, a combination of high US DAH, high funding from other donors and high GHES (one unit above their means) was associated with a 6.5% (95% Confidence Interval (CI) -73.6% to 49.6%) and a 14.6% (-86% to 60.8%) reduction in TB incidence and mortality, respectively. The corresponding decreases in incidence and mortality rates were 16.8 (-172.17 to 138.57) and 5.88 (-34.85 to 23.16) per 100 000.

CONCLUSION: Although higher US DAH, Other DAH and GHES were associated with declines in TB incidence and mortality rates, the estimated differences in TB outcomes between high-funding and low-US-DAH scenarios were small and not statistically significant.

PMID:42568929 | PMC:PMC13448635 | DOI:10.1136/bmjph-2026-005035