Regression analysis of correlated data, where multiple correlated responses are recorded on the same unit, is ubiquitous in many scientific areas. With the advent of new technologies, in particular high-throughput omics profiling assays, such correlated data increasingly consist of a large number of variables compared with the available sample size. Motivated by recent longitudinal proteomics studies of COVID-19, we propose a novel inference procedure for linear functionals of high-dimensional regression coefficients in generalized estimating equations, which are widely used to analyze correlated data. Our estimator for this more general inferential target, obtained via constructing projected estimating equations, is shown to be asymptotically normally distributed under mild regularity conditions. We also introduce a data-driven cross-validation procedure to select the tuning parameter for estimating the projection direction, which is not addressed in the existing procedures. We illustrate the utility of the proposed procedure in providing confidence intervals for associations of individual proteins and severe COVID risk scores obtained based on high-dimensional proteomics data, and demonstrate its robust finite-sample performance, especially in estimation bias and confidence interval coverage, via extensive simulations.

Infectious disease outbreaks (outbreaks) are increasing across the globe due to climate change, urbanisation and changes in land use, and many of their response measures impact risk factors for violence against women and girls (VAWG). We conducted a systematic review to consolidate existing evidence on the impact of any outbreaks, and their public health responses, on the change in magnitude of VAWG and mechanisms facilitating violence among women and girls in low-income and middle-income countries. Though our search strategy aimed to capture studies from any outbreak since 2014, all quantitative evidence on VAWG impacts, and all but one qualitative study, focused on the COVID-19 pandemic, and only three studies disaggregated outcomes for women versus girls. Overall, our synthesis of the evidence points to increased VAWG during the first year of the COVID-19 pandemic compared with pre-pandemic levels. We identified five broad mechanisms through which violence occurred against women and girls: (1) income loss due to economic shutdown, financial insecurity, and/or job loss, (2) movement restrictions, (3) changes in access to public services, (4) fear of exposure to infectious disease, and (5) a legacy of mistrust in health systems from previous outbreaks. Our study demonstrates the novelty of VAWG monitoring during outbreaks, the need for increased surveillance and the known mechanisms to date through which VAWG may be perpetrated during outbreaks. By implementing both short-term protective measures and long-term structural reforms, outbreak responses may not only break the cycle of VAWG exacerbated by public health emergencies but build resilient systems that protect women, girls and marginalised populations before, during and after crises.

To explore families' experiences participating in a 10-week web-based lifestyle programme for school-aged children with overweight or obesity.

A qualitative study using inductive analysis of semi-structured interview data.

Victoria, Australia.

Families (children aged 7-13 years with overweight or obesity-body mass index ≥85th percentile-and accompanying parent) recruited for a randomised controlled trial that evaluated the effectiveness of the web-based programme and who received the programme (n=102 children/85 families) were invited to participate in a semi-structured interview at 3 months post-programme.

Families received a 10-week family-focused electronic health (e-Health; web-based) lifestyle programme with health coaching sessions-an evidence-based programme adapted from its in-person, group-based counterpart.

A total of 28 families, including 34 children (eight siblings) and mostly mothers, shared their experiences. 10 themes were identified on family members' experiences and aligned with the socioecological model: intrapersonal-knowledge development on healthy living; experiences and stigma related to overweight, obesity or weight; engaging with structural features of the web-based programme, interpersonal-family dynamic; connections with others (non-healthcare professionals) outside of home; relationship with healthcare professionals, environmental/institutional-impact of COVID-19 lockdowns; health-promoting environments; promotion of and access to overweight or obesity management programmes; web-based programme as part of a larger or established system. Each theme highlighted factors that influenced programme uptake and engagement.

Valuable insights were gained on ways to better adapt e-Health (web-based) lifestyle programmes for children with overweight or obesity. Families perceived advantages in a web-based lifestyle programme and highly regarded humanised features and elements comparable to conventional in-person programmes. Further research is needed to explore the perspectives of families from diverse populations, fathers and families who decline participation in the follow-up period. Web-based lifestyle programmes that incorporate contemporary e-Health technologies, including responsive AI, also warrant further investigation to maximise programme benefits.

ACTRN12621001762842.

The COVID-19 pandemic underscored that access to reliable and expert-driven scientific information is not only essential but also lifesaving. Since 2020, the Italian Society of Pharmacology has been publishing SIF Magazine, an online magazine dedicated to citizens. This journal was created to make pharmacology accessible to the public, highlighting its impact on health and quality of life while clarifying the truths, theories, and misconceptions surrounding drugs and their use.

This work analyzed web interaction data from SIF Magazine to understand how the public reaches and engages with an online scientific journal and gather practical insights for improving digital scientific communication.

The data analyzed in this study were obtained from the web analytics of the SIF Magazine website. The analysis covers 3 years (2022-2024). By studying patterns of access, navigation, and engagement, the analysis clarified which types of scientific content connect most with users, how people find and choose trustworthy sources, and what they do after reaching them.

Average monthly site visits increased from 120,024 in the partial period examined in 2022 to 128,059 in 2023 and 200,379 in 2024, paralleled by higher monthly views (155,785 in 2022, 165,438 in 2023, and 254,297 in 2024). The engagement rate declined modestly (36% in late 2022, 35% in 2023, and 29% in 2024), consistent with scale-related dilution from an expanding top-of-funnel audience. Category-level analyses of top-performing articles indicated disproportionate interest in renal, urogenital, and sexual disorders followed by inflammation and pain and gastrointestinal diseases. Seasonal analyses showed recurrent peaks for season-linked topics (eg, motion sickness, photosensitivity reactions, and influenza vaccination) during expected periods.

Together, these findings underscore the importance of data-driven content planning and continuous performance monitoring to sustain the effectiveness of digital scientific communication platforms.

Early detection of health threats is an objective of public health surveillance, and event-based surveillance (EBS) using unstructured information from diverse sources has played an increasingly important role in achieving this objective. However, the evaluation of EBS systems has been hindered by the lack of reference data on outbreak onsets.

We introduce the concept of an "early detection interval" and create a dataset of these intervals across multiple countries for the epidemic caused by the Omicron variant of SARS-CoV-2.

We defined the early detection interval as the time between the date of introduction of an infectious agent to a country and the date at which an increase is detectable in traditional public health surveillance data. To determine the date of the introduction of the Omicron variant, we analyzed phylogenetic studies and genome databases. We estimated the end of the interval by applying Bayesian online change point detection to reported COVID-19 case counts. In addition to the early detection intervals, this dataset also contains variables indicating data quality. To further understand the variation in the lengths of the early detection intervals, stratified analysis and univariate Cox proportional hazards were implemented.

This dataset contains early detection intervals for the Omicron variant in 117 countries. The intervals have a median length of 28 (IQR 18-44) days, with a median beginning date of November 27, 2021 (IQR November 17, 2021, to December 12, 2021), and a median ending date of January 2, 2022 (IQR December 19, 2021, to January 9, 2022). Countries with high sequencing availability tend to have earlier start dates with a maximum difference across data sources of only 15 (IQR 7-39) days and consequently a prolonged interval length with a median length of 29 (20-47) days. Countries with low incomes were underrepresented in this dataset, with only 12 (29.27%) out of 41 included, and they tended to have shorter intervals with a median duration of 16 (IQR 12-23) days. The univariate Cox proportional hazards ratio regression analysis confirmed prolonged interval length in countries with high sequencing availability (hazard ratio 0.59, 95% CI 0.38-0.92) and shortened interval length in low-income countries (hazard ratio 2.37, 95% CI 1.29-4.36).

The dataset of early detection intervals created in this study can serve as reference data and facilitate the evaluation of the timeliness of alerts generated by EBS systems. Systematic and comprehensive evaluation of EBS is important to guide the development of EBS and motivate the integration of EBS into public health practice. Our study also highlights cross-country disparities in data quality, particularly for genomic evidence, and the need for data collection and sharing focused on low-resource settings.

Mental health issues such as depression, loneliness, and cognitive decline are prevalent among older adults. They are particularly pronounced in rural areas due to socioeconomic disadvantages, limited health literacy, and social isolation. These challenges have been exacerbated by the COVID-19 pandemic, highlighting the urgent need for accessible, community-based mental health strategies. Social prescribing-linking individuals to nonmedical community resources-offers a promising model, especially when coupled with culturally relevant and digitally facilitated interventions.

This study aimed to evaluate the effectiveness of a pilot social prescribing project for individuals aged 65 years and older residing in rural South Korea. Specifically, it examined the changes in social support, loneliness, depression, cognitive function, and life satisfaction among the older adults before and after the intervention and the relationships among these factors.

A quasi-experimental, nonequivalent control group pretest-posttest design was conducted with 294 participants from Wonju City, Gangwon-do (n=148 in the experimental group, n=146 in the control group). The 8-week intervention featured a community-based music storytelling program incorporating local cultural elements and digital education. Statistical analyses, including t tests, difference-in-differences analysis, and structural equation modeling, were conducted to evaluate changes in scores and the effectiveness of the program intervention.

The study confirmed that the social prescribing pilot project effectively reduced depression and increased social support and life satisfaction compared with the control group (P<.05, 95% CI). While cognitive function showed slight improvement, the change was not statistically significant. Social support emerged as a key mediating factor, positively influencing cognitive function and life satisfaction, and was negatively associated with depression. There was no statistically significant direct effect found between loneliness and cognitive function or social support.

This pilot study supports the feasibility and mental health benefits of integrating community and digital support through culturally embedded social prescribing for rural older adults. The findings highlight the importance of leveraging local resources and social networks to address mental health disparities in underserved aging populations, offering valuable insights for policymakers and practitioners developing inclusive aging and health promotion strategies.

In recent decades, the decline in vaccination coverage has garnered global attention, and the impact of vaccine hesitancy has become a significant concern for public health policymakers worldwide. This study aims to measure vaccine hesitancy and its associated factors among residents of Campo Grande, Mato Grosso do Sul, Brazil. From September 2022 to October 2023, a cross-sectional study aligned with a household survey was conducted to measure vaccination coverage among residents of Campo Grande municipality in Brazil. Data were collected through face-to-face interviews using the WHO. Reasons for vaccine hesitancy were classified under the 3C conceptual model of vaccine hesitancy determinants. Descriptive statistics were employed to characterize the study population, and univariate and multivariate logistic regression analyses were conducted to assess the association between hesitant and non-hesitant participants and the study variables. We included 467 households in the study, with a total of 518 participants interviewed. Over half of the participants hesitated to get vaccinated (50.2%), with the COVID-19 vaccines being the most hesitated (55.4%). The majority of reported reasons for hesitancy were related to a lack of confidence (62.3%). The hesitant participants in our study were younger than the non-hesitant participants (aOR = 0.98; 95% CI: 0.97, 0.99), were less likely to believe that vaccines could protect themselves and their children from serious diseases (aOR = 0.23; 95% CI: 0.06, 0.66), and were less likely to get information from healthcare workers or official health organizations' online profiles (aOR = 0.39; 95% CI: 0.17, 0.86). We observed a high prevalence of vaccine hesitancy in Campo Grande. The results highlight the potential impact of the COVID-19 pandemic and the infodemic in increasing negative feelings about vaccines.

Regional anesthesia is widely regarded as one of the safest anesthetic techniques, yet serious complications-such as nerve injury, hematoma, pneumothorax, and local anesthetic systemic toxicity (LAST)-continue to be reported. Their true incidence remains uncertain, as available data are often derived from registry or retrospective studies with heterogeneous definitions and limited sample sizes. Moreover, the mechanisms underlying complications such as nerve injury are incompletely understood and may extend beyond direct mechanical trauma to include factors such as sub-perineural injection, hematoma formation, altered coagulation, and patient-specific vulnerability.

The NEURAL study, promoted by the Italian Society of Anesthesia, Analgesia and Critical Care (SIAARTI), is a multicenter, prospective, observational study designed to determine the incidence and risk factors for complications following single-shot regional anesthesia of the upper limb, lower limb, and fascial plane. The primary endpoint is the composite incidence of nerve injury, hematoma, pneumothorax, and LAST. Secondary objectives include determining the individual incidence of each complication and identifying patient- and procedure-related risk factors. Data will be collected via the REDCap® (Research Electronic Data Capture) platform from more than 40 Italian centers. Standardized follow-up will be performed at 24 and 48 hours, 15 and 30 days, and monthly thereafter for unresolved neurological deficits, up to one year. Statistical analyses will include logistic regression modeling to identify independent predictors of complications.

Based on an estimated complication rate of 0.5%, a minimum of 3,396 patients will be required to ensure adequate precision of incidence estimates. Nationwide participation is expected to exceed this target.

The NEURAL study will provide robust, prospective, and standardized data on complications of regional anesthesia. By identifying their true incidence and modifiable risk factors, the findings are expected to inform safer clinical practice, enhance patient counseling, and support the development of updated evidence-based guidelines.

Across the globe, rates of depression and anxiety have risen substantially since the COVID pandemic. Consequently, poor mental health is now a top health policy priority in many countries and more people than ever are seeking treatment. While the segment of people with poor mental health is large and growing, there is a dearth of data about their demographics and health needs and their use of and experience in the health system. Health systems require this information to effectively organize and provide services.

We investigated population prevalence of fair or poor mental health and compared health system experience and quality of care among adults with poor versus good mental health in 18 high-, middle-, and low-income countries using data from the People's Voice Survey (n = 32,419). Data were collected in 2022 and 2023 through a combination of nationally representative telephone, online, and in-person surveys. Prevalence of self-reported poor mental health ranged from 4.7% in Nigeria to 39.6% in China and was unrelated to national income per capita. More women than men reported poor mental health in most countries. Across all countries, people with poor mental health had worse self-rated overall health and more chronic illness. Between 0.9% (Lao PDR) and 52.4% (UK) of those with poor mental health had received mental healthcare in the past year. People with poor mental health reported lower patient activation, worse care quality, and lower confidence in the health system. A study limitation is that results are based on self-reported mental health rather than clinical diagnoses.

People with poor mental health have markedly different health profiles and health system experience. These findings should prompt health systems to re-assess their services to better serve this growing patient group. Comparison of user experience and quality over time and across countries with similar health systems may assist in benchmarking performance.

To address high rates of diet-related disease, the UK Government has a series of voluntary targets for retailers, manufacturers, and the out-of-home sector (e.g., restaurants), to reduce the sugar, salt, and calorie content of food products. The sugar targets were intended to be met in 2020, the salt targets in 2024, and the calorie targets in 2025 (extended from 2024 due to Covid-19). There is limited evidence for how the out-of-home sector is performing against these targets, and individual company responses have not been evaluated. This study aimed to assess adherence to UK Government's sugar, salt, and calorie reduction targets for menu items offered by the 21 highest-grossing restaurant chains in 2024.

Nutritional information was collected from restaurants' online menus. Mean/median sugar, salt, and calorie content, per 100 g and per serving, was calculated for each restaurant and food subcategory. Sugar, salt, and calorie content for each menu item was compared against the UK Government's targets, and the proportion of menu items meeting (i) each and (ii) every applicable target, was calculated for each restaurant and food subcategory. Three thousand ninety-nine menu items were included. Across all restaurants, 61% of menu items met their calorie targets, 58% met their salt targets, 36% met their sugar targets, and 43% met all of their applicable targets. Six of the 12 food subcategories, and nine of the 21 restaurants, had over 50% of menu items meeting all of their applicable targets. Menu items from Papa John's were the lowest adhering for the calorie (35%) and salt (8%) targets, and menu items from Burger King, KFC, Nando's, and Vintage Inns were the lowest adhering for the sugar targets (0%). Menu items from pizza restaurants had the lowest adherence to all applicable targets (32% overall) out of all the restaurant types, but items offered by restaurants with similar menu foci were also found to vary in their adherence. We were unable to account for heterogeneity in item-level sales due to the lack of accessible sales data from the out-of-home food sector, and therefore we could only assess performance against the targets for available items as opposed to purchased items.

Our findings suggest that while menu items from certain restaurant types appear to perform worse than others against the sugar, salt, and calorie targets, items from restaurants with similar menu portfolios also vary in their adherence, highlighting the potential for restaurants to improve the nutritional quality of their products without changing their menu focus. Our study demonstrates that there is low adherence to voluntary schemes across the out-of-home sector, and therefore mandatory regulations may be a more effective approach to improving the nutritional quality of out-of-home food.