Category: Statistics

JMIR Public Health Surveill. 2025 Sep 29;11:e69655. doi: 10.2196/69655.

ABSTRACT

BACKGROUND: Effective disease surveillance is essential for understanding pathogens’ epidemiology, detecting outbreaks, and enabling timely public health responses. In the United Kingdom, large-scale studies, such as the Office for National Statistics COVID-19 Infection Survey (CIS), have monitored SARS-CoV-2 transmission but required significant resources, making them challenging to sustain when pandemic-specific funding ends and also in resource-limited settings. In contrast, the Virus Watch study, at lower cost, relied on self-reported and linked national testing data as well as symptomatic testing, while Severe Acute Respiratory Infections Watch (SARI) leveraged hospital data for cost-effective surveillance.

OBJECTIVE: This study aimed to evaluate the effectiveness of Virus Watch as a surveillance system in monitoring COVID-19 positivity, incidence, and hospitalization rates in England and Wales, using data from the CIS and SARI as benchmarks for comparison, while considering the key differences in the study designs, including recruitment strategies, incentives, and testing criteria.

METHODS: We used the Virus Watch prospective community cohort study to estimate COVID-19 positivity, incidence, and hospitalization rates in England and Wales from June 2020 to March 2023. Rate estimates were compared with CIS modeled positivity and incidence rates, and with SARI COVID-19 hospitalization rates. Global synchrony between datasets was measured using overall Spearman ⍴ and local synchrony using 9-week rolling Spearman ⍴. For England, comparisons with CIS estimates used Virus Watch rates calculated with and without linked national testing data. Positivity rates were also assessed overall and separately before and after the end of free national testing.

RESULTS: A total of 58,628 participants were recruited into the Virus Watch study, of whom 52,526 (89.6%) were resident in England and 1532 (2.6%) in Wales; region was missing for the remainder. Virus Watch-estimated COVID-19 positivity and incidence rates in England, calculated with and without linked testing data, showed strong global synchrony with CIS estimates (positivity ⍴: 0.91 and 0.90; both P<.001 and incidence ⍴: 0.92 and 0.90; both P<.001) and strong local synchrony (positivity ⍴: median 0.75, IQR 0.53-0.85 and median 0.67, IQR 0.47-0.83, and incidence ⍴: median 0.76, IQR 0.49-0.88 and median 0.66, IQR 0.45-0.82), despite having lower absolute values. Global and local synchrony of positivity rates were similar for periods before and after the end of free national testing, although the difference between Virus Watch and CIS estimates was greater post-free testing. COVID-19 hospitalization rates were also lower and less synchronized with SARI estimates. In Wales, Virus Watch estimates exhibited greater variability (positivity ρ: 0.75, P<.001; incidence rate ρ: 0.85, P<.001) and lower local synchrony (positivity ρ: median 0.61, IQR 0.34-0.74, and incidence ρ: median 0.52, IQR 0.38-0.71) compared to England.

CONCLUSIONS: Our results highlight the effectiveness of the Virus Watch approach in providing accurate estimates of COVID-19 positivity and incidence rates, even in the absence of national surveillance systems. This low-cost method can be adapted to various settings, particularly low-resource ones, to strengthen public health surveillance and inform timely interventions.

PMID:41021969 | DOI:10.2196/69655

IEEE Trans Biomed Eng. 2025 Sep 29;PP. doi: 10.1109/TBME.2025.3615514. Online ahead of print.

ABSTRACT

Scaling neural recording systems to thousands of channels creates extreme bandwidth demands, posing a challenge for resource-constrained, implantable devices. This work introduces an adaptive, multi-stage compression framework for high-bandwidth neural interfaces. The system combines a Wired-OR analog-to-digital compressive readout with a digital core that adaptively requantizes, selectively samples, and encodes the neural signals. Although prior work suggests that action potential recordings can be re-quantized to approximately the signal-to-noise (SNR) number of bits without significantly degrading decoding performance, our results show that the required resolution can often be reduced even further. By matching the number of quantization levels to the electrode’s maximum SNR ($bm {lceil log _{2} rm{SNR} rceil }$ number of bits), we retain waveform fidelity while eliminating unnecessary precision that primarily captures noise. Recorded spike samples are selected using a mutual information-based criterion to preserve both spatial and temporal discriminative waveform features. A static entropy coder completes the pipeline with low computation overhead compression optimized for neural signal statistics. Evaluated on 512-channel macaque retina ex vivo data, the system preserves 90% of spikes while achieving a 1098× total compression over baseline.

PMID:41021967 | DOI:10.1109/TBME.2025.3615514

IEEE J Biomed Health Inform. 2025 Sep 29;PP. doi: 10.1109/JBHI.2025.3614093. Online ahead of print.

ABSTRACT

Visceral adipose tissue (VAT) is a key marker of both metabolic health and habitual physical activity (PA). Excess VAT is highly correlated with type 2 diabetes and insulin resistance. The mechanistic basis for this pathophysiology relates to overloading the liver with fatty acids. VAT is also a highly labile fat depot, with increased turnover stimulated by catecholamines during exercise. VAT can be measured with sophisticated imaging technologies, but can also be inferred directly from PA. We tested this relationship using National Health and Nutrition Examination Survey (NHANES) data from 2011-2014, for individuals aged 20-60 years with 7 days of accelerometry data (n=2,456 men; 2,427 women) [1]. Two approaches were used for estimating VAT from activity. The first used engineered features based on movements during gait and sleep, and then ridge regression to map summary statistics of these features into a VAT estimate. The second approach used deep neural networks trained on 24 hours of continuous accelerometry. A foundation model first mapped each 10 s frame into a high-dimensional feature vector. A transformer model then mapped each day’s feature vector time series into a VAT estimate, which were averaged over multiple days. For both approaches, the most accurate estimates were obtained with the addition of covariate information about subject demographics and body measurements. The best performance was obtained by combining the two approaches, resulting in VAT estimates with correlations of r=0.86. These findings demonstrate a strong relationship between PA and VAT and, by extension, between PA and metabolic health risks.

PMID:41021956 | DOI:10.1109/JBHI.2025.3614093

IEEE Trans Neural Syst Rehabil Eng. 2025 Sep 29;PP. doi: 10.1109/TNSRE.2025.3615417. Online ahead of print.

ABSTRACT

Chronic low back pain (LBP) significantly impairs daily functional movements. Persistent pain may trigger alterations in neuromuscular control, particularly muscle coordination. However, muscle synergy patterns during specific functional tasks in patients with LBP remain unclear. We recruited 36 participants, including 18 patients with chronic LBP (the LBP group) and 18 healthy participants (the control group). Surface electromyography signals were recorded from ten trunk and lower-limb muscles during three common functional tasks: sit-to-stand, trunk flexion, and lifting. Muscle synergies were extracted via non-negative matrix factorization. Cosine similarity analysis and statistical parametric mapping were applied to evaluate spatial (motor modules) and temporal (motor primitives) differences between groups. Compared to the control group, participants with chronic LBP exhibited a reduced number of muscle synergies during sit-to-stand, indicating adaptive reorganization of motor modules. Although spatial muscle synergy structures were largely conserved between groups, significant temporal differences emerged in trunk flexion, particularly during eccentric phases. Patients with LBP showed prolonged and temporally shifted activation of spinal extensors and hip-pelvic stabilizers, suggesting compensatory mechanisms to mitigate spinal loading. Muscle contribution patterns during lifting tasks also differed significantly between groups, despite similar temporal activation. In conclusion, patients with chronic LBP demonstrate distinct muscle synergy adaptations characterized by reduced complexity, altered timing during eccentric trunk movements, and modified lower-limb recruitment strategies. Trunk flexion emerged as a particularly sensitive task for identifying neuromuscular deficits in LBP. These findings provide targeted insights for clinical rehabilitation, emphasizing eccentric trunk control, motor control timing, and lower-limb muscle retraining.

PMID:41021946 | DOI:10.1109/TNSRE.2025.3615417

Med Sci Sports Exerc. 2025 Sep 25. doi: 10.1249/MSS.0000000000003856. Online ahead of print.

ABSTRACT

OBJECTIVES: To compare brain MRI outcomes between children who play American football vs non-contact sport controls testing the hypotheses that history (primary) and duration (secondary) of football participation would be associated with differences in cortical thickness, subcortical volume, resting state functional connectivity, and white matter diffusivity.

METHODS: This secondary analysis of cross-sectional baseline data from the Adolescent Brain Cognitive Development (ABCD) Study compared brain MRI outcomes between 9-10 year-old children who play American football (n=1194) vs. non-contact sport controls (n=807). Outcomes included 74 bilateral cortical thickness regions; 10 gray matter subcortical volumes, with a priori focus on the hippocampi; resting-state functional connectivity (169 network-network correlations and 247 network-region correlations across 13 resting-state functional networks and 19 regions); and 21 diffusion tensor measures.

RESULTS: Football participation was associated with global effects on cortical thickness (p=0.017), network-to-network resting state connectivity (p=0.010), and fiber tract volume (FDR-adjusted p=0.015) in primary analysis, but the only significant post-hoc finding after FDR correction was smaller cortical thickness adjacent to the left anterior transverse collateral sulcus in the football group (Cohen D=-0.258, FDR-adjusted p=0.017). There were no significant duration of football play effects in secondary analyses (all p>0.05). Targeted analysis of hippocampal volumes yielded no significant football or duration of play results (both p>0.05), but suggested a potential trend of lower hippocampal volumes with increasing duration of play.

CONCLUSIONS: At ages 9-10, participation in American football was associated with minimal differences across a large array of structural, functional, and diffusion tensor MRI outcomes. While the clinical implications of these cross-sectional results are unknown, they merit additional investigation and can contribute to the ongoing discussion surrounding contact sport participation in children.

PMID:41021925 | DOI:10.1249/MSS.0000000000003856

J Med Internet Res. 2025 Sep 29;27:e74226. doi: 10.2196/74226.

ABSTRACT

BACKGROUND: The Ministry of Health Malaysia integrated the Casemix System into the Total Hospital Information System (THIS) to improve care delivery, resource efficiency, and cost-effectiveness. Casemix, a patient classification tool, supports clinical documentation, hospital financing, and management by grouping patients according to diagnoses and resource use. Within THIS, it enables automated coding, streamlined workflows, and better hospital performance. Its success, however, relies on acceptance by medical doctors who ensure accurate documentation and coding. Despite its importance, limited empirical research has examined factors influencing Casemix acceptance in Malaysia’s hospital information system context. Understanding these factors is critical for effective implementation and sustained use.

OBJECTIVE: This study aims to investigate the interrelationships between critical success factors namely system quality (SY), information quality (IQ), service quality (SQ), organizational characteristic (ORG), perceived ease of use (PEOU), perceived usefulness (PU), and intention to use (ITU) on user acceptance of the Casemix system in hospitals equipped with THIS.

METHODS: This study used a cross-sectional design, using a self-administered digital questionnaire that was developed by adopting and adapting previously validated instruments, grounded in the Human-Organization-Technology Fit and Technology Acceptance Model (TAM) frameworks. The instrument underwent rigorous validation and reliability procedures, including content and criterion validation through expert review, exploratory factor analysis to assess item appropriateness, and confirmatory factor analysis to establish construct, convergent, and discriminant validity. Proportionate stratified random sampling was used to ensure equitable representation of medical doctors across 5 Ministry of Health hospitals, each representing 1 of Malaysia’s geographical zones. The minimum required sample size of 375 was proportionally distributed across 4 categories of medical doctors within these hospitals. Based on structural equation modeling standards, a total of 343 valid responses were obtained, yielding a response rate of 91.5%. Path analysis was conducted using covariance-based structural equation modeling with SPSS Amos (version 24.0; IBM Corp) to assess the direct relationships among the constructs in this study.

RESULTS: Path analysis revealed that SY (β=-0.262, P=.043) and IQ (β=0.307, P=.01) significantly influenced PEOU. PEOU (β=0.105, P=.02) and PU (β=0.580, P<.001) significantly influenced ITU, which strongly predicted user acceptance (β=0.788, P<.001). PEOU did not substantially impact PU (β=0.086, P=.07), nor did SQ (β=0.146, P=.19) and ORG (β=0.197, P=.21) significantly influence PEOU. Based on the β coefficients and statistical significance, the critical success factors were categorized into 2 groups: higher-ranked predictors (ITU, PU, IQ, and SY) and lower-ranked predictors (ORG, SQ, and PEOU). Higher-ranked predictors demonstrated statistically significant relationships and relatively stronger β coefficients.

CONCLUSIONS: This study offers empirical insights into key factors influencing Casemix system acceptance and informs strategies to support its successful implementation in THIS-equipped hospitals. The findings also contribute to addressing current research gaps and guiding future evaluations of health care information systems.

PMID:41021917 | DOI:10.2196/74226

J Med Internet Res. 2025 Sep 29;27:e67640. doi: 10.2196/67640.

ABSTRACT

BACKGROUND: Nutrition misinformation is pervasive on frequently accessed online sources such as social media platforms and websites. Young adults are at a high risk of viewing or engaging with this content due to their high internet and social media usage.

OBJECTIVE: This study aimed to understand young adults’ preferences, perceptions, and use of online nutrition content.

METHODS: Young Australian adults (aged 18-25 years) were recruited and interviewed individually via video calling (Zoom; Zoom Video Communications) between December 2023 and February 2024. Participants were recruited via convenience sampling using Facebook advertising. The interviewer followed a semistructured format, and questions were guided using a piloted template. Reflexive thematic analysis was conducted using NVivo (Lumivero) to explore the preferences, perceptions, and use of online nutrition content among the sample.

RESULTS: The sample (N=20; mean age 22.9 y, SD 2.3 y) was predominantly female (n=13, 65%) and had, or was studying toward, a tertiary qualification (16/17, 94%). Most participants used social media (19/20, 95%) and internet websites (16/20, 80%) to access nutrition content. Other platforms used included generative artificial intelligence (n=1), apps (n=1), eBooks (n=1), newsletters (n=1), and podcasts (n=1). When exploring perceptions, most participants agreed that online nutrition content was quick and easy to find and informative. Furthermore, perceived reliability and engagement depended on several factors such as the creator’s credentials, length and format of content, consensus on topics, and sponsorships. Short-form content was not considered reliable, despite its engaging nature. Content containing sponsorships or product endorsements was met with skepticism. However, participants were more likely to trust content reportedly created by health professionals, but it was unknown whether they were accessing verified professionals. The oversaturation of content demotivated participants from evaluating the reliability of content. When asked about preferences, participants valued both short- and long-form content, and evidence-based content such as statistics and references and preferred casual and entertaining content that incorporated high-quality and dynamic editing techniques such as voiceovers.

CONCLUSIONS: The study identified the online nutrition content sources and topics young Australian adults access and the key factors that influence their perceptions and preferences. Young Australian adults acknowledge that misinformation is not exclusive to certain platforms. The accessibility and engagement of content and the ambiguity of professional “credentials” may lead them to trust information that is potentially of low quality and accuracy. Findings also show that there needs to be a balance between engaging formats and presenting evidence-based information when designing online nutrition content to engage these audiences while combatting nutrition misinformation. Future research should explore how these factors impact usage of online nutrition content and dietary behaviors among young Australian adults. Further consultation with this cohort can inform tailored interventions that aim to enhance their food and nutrition literacy and diet quality.

PMID:41021916 | DOI:10.2196/67640

JMIR Infodemiology. 2025 Sep 29;5:e65319. doi: 10.2196/65319.

ABSTRACT

BACKGROUND: Cannabis is the third most consumed drug worldwide, with its use linked to a high number of substance use disorders, particularly among young men. Associated mortality causes include traffic accidents and cardiovascular diseases. The global expansion of cannabis legalization has sparked debates about its impact on risk perception, with risk perception decreasing in countries with permissive laws. Social media analysis, such as on Twitter (subsequently rebranded as X), is a useful tool for studying these perceptions and their variation by geographic region.

OBJECTIVE: This study aims to analyze Twitter users’ perceptions of cannabis use and legalization, taking into account the geographic location of the tweets.

METHODS: A mixed methods approach was used to analyze cannabis-related tweets on Twitter, using keywords such as “cannabis,” “marijuana,” and “hashish.” Tweets were collected from January 1, 2018, to April 30, 2022, in English and Spanish, and only those with at least 10 retweets were included. The content analysis involved an inductive-deductive approach, resulting in the classification of tweets into thematic categories, including discussions on legalization.

RESULTS: The tweet analysis showed that in America, Europe, and Asia, political discussions about cannabis were the most common topic, while personal testimonies dominated in Oceania and Africa. In all continents, personal experiences with cannabis use were mostly positive, with Oceania recording the highest percentage (1642/2695, 60.93%). Regarding legalization, Oceania also led with the highest percentage of tweets in favor (1836/2695, 68.13%), followed by America and Africa, while support in Europe and Asia was slightly lower, with about half of the tweets in favor.

CONCLUSIONS: The political debate has been the most frequently mentioned topic, reflecting the current situation in which legislative changes are being discussed in many countries. The predominance of opinions in favor of legalization, combined with the prevalence of positive experiences expressed about cannabis, suggests that the health risks associated with cannabis use are being underestimated in the public debate.

PMID:41021906 | DOI:10.2196/65319

Natl Vital Stat Rep. 2025 Sep 16;(10):1. doi: 10.15620/cdc/174607.

ABSTRACT

OBJECTIVES: This report presents final 2023 data on the 10 leading causes of death in the United States by age group, race and Hispanic origin, and sex. Leading causes of infant, neonatal, and postneonatal death are also presented. This report supplements “Deaths: Final Data for 2023,” the National Center for Health Statistics’ annual report of final mortality statistics.

METHODS: Data in this report are based on information from all death certificates filed in the 50 states and the District of Columbia in 2023. Causes of death classified by the International Classification of Diseases, 10th Revision are ranked according to the number of deaths. Cause-of-death statistics are based on the underlying cause of death.

RESULTS: In 2023, the ranked order of 7 of the 10 leading causes of death changed from 2022. The 10 leading causes of death in 2023 in ranked order were: Diseases of heart; Malignant neoplasms; Accidents (unintentional injuries); Cerebrovascular diseases; Chronic lower respiratory diseases; Alzheimer disease; Diabetes mellitus; Nephritis, nephrotic syndrome and nephrosis; Chronic liver disease and cirrhosis; and COVID-19. These causes accounted for 70.9% of all deaths occurring in the United States. Rankings are presented by age, race, Hispanic origin, and sex. The 10 leading causes of infant death for 2023 in ranked order were: Congenital malformations, deformations and chromosomal abnormalities; Disorders related to short gestation and low birth weight, not elsewhere classified; Sudden infant death syndrome; Accidents (unintentional injuries); Newborn affected by maternal complications of pregnancy; Bacterial sepsis of newborn; Newborn affected by complications of placenta, cord and membranes; Respiratory distress of newborn; Intrauterine hypoxia and birth asphyxia; and Diseases of the circulatory system.

PMID:41021892 | DOI:10.15620/cdc/174607

Psychol Health Med. 2025 Sep 29:1-15. doi: 10.1080/13548506.2025.2561741. Online ahead of print.

ABSTRACT

The objective of this study is to ascertain the long-term risk of obesity associated with smartphone addiction in children and adolescents. We utilized a 4-year dataset from the Korean Children and Youth Survey 2018 (2018-2021). At baseline, the sample comprised 2,607 4th-grade elementary school students and 2,590 1st-grade middle school students (mean age: 11.3 ± 0.3, 14.3 ± 0.3 years, respectively). Of these, 2,718 (52.3%) were boys. Obesity was defined as a body mass index Z-score of at least the 95th percentile according to the 2017 Korean National Growth Charts. During the four-year follow-up period, the prevalence of obesity ranged from 6.9% to 8.4%, while the prevalence of being at high risk of smartphone addiction ranged from 2.1% to 4.8%. The logistic generalized estimating equation (GEE) was employed to examine the risk of obesity in those with addiction to smartphones. The risk of obesity was analyzed by adding smartphone screen time in Model 1, smartphone addiction in Model 2, and smartphone screen time and addiction in Model 3. The GEE results indicated that the odds of obesity increased by 16% in the potential-risk group for smartphone addiction compared to the normal group, even with the same duration of smartphone usage (OR [odds ratio] = 1.16, 95% CI [confidence interval] 1.01-1.33). Although the increase was not statistically significant, the odds of obesity were 1.24 times higher in the high-risk smartphone addiction group (OR = 1.24, 95% CI 0.94-1.65). Spending more than 3 hours on a smartphone was linked to 1.37-fold higher odds of obesity compared to spending less than 1 hour (95% CI 1.14-1.63). Smartphone addiction and overuse among children and adolescents can potentially raise obesity risks. Active interventions are needed to promote healthy smartphone behaviors in children and adolescents.

PMID:41021890 | DOI:10.1080/13548506.2025.2561741