The Lancet Regional Health - Western Pacific

Purpose: This study assesses the association between colorectal cancer (CRC) screening and a validated, housing-based measure of individual-level socioeconomic status (SES, called HOUSES hereafter) within rural communities and determines whether HOUSES-integrated geospatial analysis can be used to tailor interventions. Methods: We used CRC screening data from a subset of Mayo Clinic Midwest patients living in cities without ready access to routine care in the Mayo Clinic Health System in 2019 to represent rural communities. At the individual level, we assessed the association between CRC screening rates and the HOUSES index, adjusting for age, sex, race/ethnicity, comorbidity, distance from home address to clinic, and area deprivation index, using a multilevel mixed-effects logistic regression model. Additionally, we conducted geospatial analysis to examine the correlation between hotspots of 1) lower CRC screening rates and 2) lower SES of the subject population (HOUSES quartile 1). Findings: Among 34,489 individuals (median age 64.0 years, 52.4% female), those with the lowest SES (HOUSES Q1) had 37% lower odds of being CRC screening adherent than those with the highest SES (HOUSES Q4) (adj. OR [95% CI]: 0.63 [0.58-0.69]). In the 14 identified HOUSES Q1 hotspots, there was a significant correlation in counts of HOUSES Q1 and low CRC screening (correlation coefficient=0.81). Conclusion: Lower SES was significantly associated with lower CRC screening among rural populations. HOUSES-enabled geospatial analysis identified geographic hotspots with lower CRC screening rates for targeted interventions to address disparities in CRC screening in rural communities. HOUSES may be a useful digital tool for cancer preventive care and research.

Carbapenem-resistant Escherichia coli (CR-E. coli) is an emerging One Health threat, but recent shifts in predominant lineages and genomic links between clinical and food reservoirs in Hong Kong remain poorly defined. We analyzed 271 CR-E. coli isolates from four hospitals (2022-2026) and 585 isolates recovered from 4,917 retail food samples (2022-2025). Isolates underwent antimicrobial susceptibility testing, whole-genome sequencing, multilocus sequence typing, resistance-gene and plasmid profiling, core-genome SNP phylogenetics, and comparative genomics. Food isolates were mainly from raw pork (268/585, 45.8%) and raw chicken (231/585, 39.5%). blaNDM-5 was detected in 527/585 (90.1%) food and 241/271 (88.9%) clinical isolates. ST69 was the most frequent defined sequence type in both collections, representing 44/585 (7.5%) food and 36/271 (13.3%) clinical isolates, in contrast to the heterogeneous lineages and carbapenemases previously reported in Hong Kong. Applying a predefined [≤]50-pairwise-SNP threshold for close genomic relatedness, core-genome phylogeny of 80 ST69 isolates identified two major mixed-source clusters collectively comprising 28 clinical and 27 food isolates. Clustered isolates showed similar antimicrobial resistance profiles, carried blaNDM-5 and blaTEM-1, and were associated with IncI1 MLST | ST136 plasmids. Comparative analyses showed >99.85% average nucleotide identity and broad conservation of the blaNDM-5-associated plasmid backbone across sources. These findings indicate the emergence of blaNDM-5-carrying ST69 as a prominent CR-E. coli lineage in Hong Kong and demonstrate close genomic relatedness between selected clinical and retail food isolates. Although transmission direction have not been inferred yet, the findings support integrated One Health surveillance and source-tracing across clinical, food, animal, and environmental sectors.

Micronutrient deficiencies are prevalent in Madagascar, where diets rely heavily on starchy staples and access to animal-source foods is limited. Small dried fish (SDF) are widely available, yet their nutritional value and health risks remain poorly documented. We combined market surveys, taxonomic identification, and micronutrient and heavy metal analyses of nine SDF types collected along National Road 7. The samples encompassed 33 fish families, were dominated by small pelagic species (Clupeidae and Engraulidae), and were appreciated by consumers. A daily portion (5 g for infants; 10 g for young children and women of childbearing age) contributed substantially to Recommended Nutrient Intakes (RNIs). Across samples and groups, SDF were rich (>30% of RNI) in selenium and, for infants and young children, in calcium. All samples were a source of (>15% of RNI), or rich in, phosphorus, whereas iron contributions were more variable but often substantial. Several samples exceeded 100% of RNIs for selenium, calcium, iron, or manganese in infants and young children, and some were also sources of magnesium and, less frequently, zinc. Vitamin A was absent from sun-dried samples but detected in a smoked freshwater type. Heavy metal concentrations varied markedly, and portions of several types led to estimated exposures to inorganic arsenic or cadmium exceeding reference values, whereas freshwater species and some pelagic types showed a more favorable nutrition-risk balance. Overall, SDF are affordable, nutrient-dense foods with strong potential to alleviate micronutrient deficiencies in Madagascar, while highlighting the need for type-specific guidance to balance nutritional benefits and contamination risks.

Background Alcohol-associated liver disease (ALD) has emerged as a major cause of chronic liver disease and liver-related mortality in China. This study aimed to project the future burden of ALD in Chinese adults from 2020 to 2050, including prevalence of ALD, number of alcoholic steatohepatitis (ASH) cases, incident hepatocellular carcinoma (HCC) cases, liver transplantation (LT) demand, liver-related deaths, and disability-adjusted life years (DALYs). Methods We developed an agent-based state-transition microsimulation model with yearly cycles and a lifetime horizon. The model simulated 5,678,912 representative Chinese adults (mean age 36.2 years, 51.2% male). Health states included no steatosis, alcohol-associated steatotic liver, ASH, fibrosis stages F0-F4, decompensated cirrhosis, HCC, LT, and liver-related death. Model inputs were derived from the China Kadoorie Biobank, Global Burden of Disease Study 2021, China's national surveys, published meta-analyses, and transplant registry data. Projections incorporated demographic shifts, alcohol consumption trends, and calibrated transition probabilities. Uncertainty was assessed via 1,000 Monte Carlo simulations generating 95% uncertainty intervals. Results ALD prevalence was projected to increase from 4.8% (55 million individuals) in 2020 to 8.5% (94 million individuals) by 2050. ASH cases rose from approximately 18 million to 20 million. Annual incident HCC cases nearly doubled from 20,500 in 2020-2025 to 45,200 by 2046-2050. LT demand quadrupled from 2,300 to 9,800 cases. Liver-related deaths increased from 50,000 in 2020 to 85,000 in 2050, while DALYs rose from 1.5 million to 2.6 million. Conclusions In the absence of strengthened alcohol control policies, ALD will impose a substantial and growing burden on China's health system by 2050, with marked increases in HCC incidence, LT demand, and liver-related mortality.

Background Childhood respiratory mortality in China has fallen by over 90% in three decades alongside sustained national warming, yet national long-run evidence on temperature and child respiratory mortality is lacking. Methods We linked Global Burden of Disease (GBD) 2021 mortality estimates for China - lower respiratory infections (LRI), ages 0-19, and asthma, ages 0-24, 1990-2021 - with C-LSAT 0.5 deg gridded temperature data (1990-2019), aggregated nationally and to five climate zones. Four annual indicators (mean temperature, diurnal temperature range, seasonal amplitude, interannual variability) entered regressions of log mortality rates with Newey-West standard errors. A bootstrapped (500 resamples) quadratic model probed the minimum mortality temperature (MMT), with PM2.5-adjusted analyses and future-exposure, permutation, and detrended falsification tests. Results LRI deaths fell by 96.3% (330,194 in 1990 to 12,098 in 2021; 95% uncertainty interval 9,669-14,891) and asthma deaths by 94.9% (3,287 to 167), while mean temperature rose 0.364 deg C per decade and diurnal temperature range narrowed 0.092 deg C per decade. Baseline coefficients were large (mean temperature -1.696, SE 0.174; diurnal temperature range +2.408, SE 0.336; seasonal amplitude -0.162, SE 0.082; interannual variability +2.924, SE 1.514, per 1 deg C in log rate), but the future-exposure test failed and detrending nullified every coefficient: the associations are trend-level, and short-cycle causal effects are not identifiable. Nor was the national MMT identifiable - observed temperature support spans only 6.66-8.13 deg C, and the nominal turning point of 35.84 deg C is an extrapolation artifact (quadratic term p = 0.963). Within the observed range, warming and declining mortality moved in the same direction. Conclusions The 96% decline in childhood respiratory mortality cannot be attributed to warming. China sits on the low-temperature side of the optimum, and the marginal direction of future warming requires stronger designs to establish. The falsification framework offers a discipline for climate-health inference in China.

Introduction. By the end of 2023, many low-income countries had not reached 50% COVID-19 vaccine coverage, while most high-income countries had exceeded 80%. It remains unclear whether receiving vaccine deliveries translated into faster population coverage. We examined cross-national inequalities in the timing of the vaccine rollout and whether deliveries through the COVID-19 Vaccines Global Access (COVAX) facility were associated with subsequent national uptake. Methods. We conducted an observational study of 218 countries and territories using country-level data up to December 2023. We used generalized additive mixed models to identify country-level correlates of coverage at an early and a later stage of the pandemic, survival analysis to compare the time to 50% coverage between COVAX Advance Market Commitment (AMC) and non-AMC countries, and an event study to estimate the association between the timing of the first COVAX delivery and subsequent monthly coverage in AMC countries. Results. AMC-supported countries reached 50% coverage substantially more slowly than non-AMC countries. The hazard of reaching the threshold was 0.17 times that of non-AMC countries at month 1 (95% CI 0.07 to 0.41) and 0.53 times at month 18 (95% CI 0.33 to 0.85). One year after rollout began, 65.9% of AMC countries (95% CI 56.7 to 76.6) had not reached 50% coverage, compared with 21.1% of non-AMC countries (95% CI 15.1 to 29.5). The timing of COVAX deliveries was not significantly associated with subsequent national uptake in any post-delivery month. In the early stage of rollout, higher maternal mortality was associated with lower coverage, while a larger urban population was associated with higher coverage. By the end of the observation period, larger household size was associated with lower coverage, while higher health expenditure and a larger urban population were associated with higher coverage. Conclusion. Receiving COVAX deliveries was not, on its own, associated with faster coverage. Coverage differences were more consistently associated with country-level structural and health-system characteristics, while we found no significant association with the timing of the first COVAX delivery. Achieving vaccine equality likely requires strengthening the capacity of health systems to convert deliveries into administered doses, and preparedness efforts should invest in last-mile delivery capacity ahead of future emergencies.

Seeking a simple vaccine to protect against all cancer-associated human papillomaviruses (HPV), L2 residues 17-36 of both HPV16 and HPV31 displayed on the surface of an Adeno-Associated Virus-Like Particle (AAVLP-HPV) was developed. Here, a phase 1 randomized, placebo-controlled, double-blind clinical study has been conducted in 20 male and female subjects at a single dose level (20 ug) without an adjuvant. AAVLP-HPV vaccine administration was safe and well tolerated. Repeat vaccination with AAVLP-HPV elicited L2-specific neutralizing antibodies of modest titer in serum. Antibodies cross-reactive with L2 of diverse HPV types were detected, but responses were weak in most vaccinees. We conclude that while AAVLP-HPV vaccination is well tolerated, an adjuvant is likely needed to consistently elicit durable and broadly neutralizing responses.

Introduction Patients undergoing polypectomy at colonoscopy remain at risk of metachronous neoplasia despite surveillance guided by histopathological features. Mutational profiling of adenomas, including canonical driver mutations in APC, KRAS, and TP53, may offer additional predictive value. This study aimed to determine whether mutational status in index adenomas was associated with metachronous lesion risk. Methods The INCISE cohort included patients aged 50 to 74 years who underwent polypectomy within the Scottish Bowel Screening Programme and subsequent surveillance colonoscopy within 6 years. Targeted next-generation sequencing was performed on formalin-fixed paraffin-embedded polyps. Driver mutation frequency, tumour mutational burden (TMB), and variant allele frequency (VAF) were analysed and correlated with histopathological features and metachronous outcomes using appropriate statistical models. Results A total of 895 adenomas from 723 patients were analysed. In conventional adenomas, as the number of high-risk histopathological features (size >=10mm, villous architecture, and high-grade dysplasia) increased there was a stepwise increase in the proportion of samples with a mutation in KRAS from 13% to 51% (padj<0.001) and TP53 from 8% to 35% (padj<0.001). However, neither mutation frequency (p=0.901), nor median tumour mutation burden (TMB) (2.27 vs 2.15 mut/Mb, p=0.242), in index adenomas was associated with the development of metachronous lesions. Conclusions While classical driver mutations reflect histopathological progression within adenomas, they do not predict metachronous lesion risk post-polypectomy. Targeted mutation profiling alone is insufficient for surveillance risk stratification, highlighting the need for integrated molecular approaches in this setting.

The persistence of Plasmodium vivax is driven by the hidden reservoirs of infection, presenting a key obstacle to elimination. Antibodies persist after asexual infections are cleared from peripheral blood and therefore can indicate current and recent past infections. Here, we present a machine learning algorithm that classifies recent P. vivax infections using serological markers to identify likely hypnozoite carriers. Using serological measurements from year-long observational cohort studies conducted in three low-transmission settings (including negative controls, N=2,635), we selected optimal subsets of markers by balancing sero-diagnostic performance against assay complexity and scalability. We initially trained a random forest classifier and then subsequently we compared several machine learning classifiers. Tree-based methods consistently performed best, although differences were marginal. An online R Shiny application (PvSeroApp) was developed to automate data processing, quality control, and serostatus classification. This algorithm underpins the P. vivax serological testing and treatment (PvSeroTAT) strategy, enabling targeted anti-hypnozoite therapy and strengthening elimination efforts.

Abstract Background The gut microbiome has been widely studied in the context of obesity, and yet the reported associations vary widely across populations and analytical approaches. In Asian populations where the prevalence of obesity is rapidly rising, the extent to which gut microbiome features could associate with adiposity in a robust and generalizable manner remains unclear. Methods Population-scale shotgun metagenomic data was generated for adults (n=871) from the Health for Life in Singapore (HELIOS) cohort, comprising ethnic Chinese, Malay, and Indian participants. Integrated taxonomic, functional, and machine-learning-based analyses were used to assess associations between gut microbiome features and obesity, adjusting for demographic covariates and evaluating for robustness across multiple statistical frameworks. Results Global microbiome structure exhibited weak separation by body mass index (BMI), with enterotype-like clustering providing limited discriminatory power for obesity status. Differential abundance analyses identified a small number of method-dependent taxa and pathways, with only limited recurrence across methods. Supervised machine learning models trained on taxonomic profiles achieved modest predictive performance, particularly for intermediate BMI classes, and did not reveal robust microbial signatures beyond those detected by univariate analyses. Conclusions Our study highlights the importance of large-scale, multi-framework analyses for distinguishing robust microbiome-phenotype associations from weak, method-dependent signals. Together, our findings emphasize that obesity-associated microbiome signatures may be too weak, diffuse, and insufficient to explain adiposity in Asian populations.

Background Trial participation effect, defined as a change in clinical outcomes associated with trial enrolment regardless of allocation, is understudied in neonatal trials in low- and middle income countries (LMIC), despite its importance for trial design, interpretation, and research ethics. This study aimed to quantify the trial participation effect and explore potential ways by which research participation may influence neonatal survival. Methods This observational cohort study included neonates weighing <2Kg and aged <24h who were admitted to a Gambian referral hospital and either enrolled in a clinical trial comparing early versus later KMC (eKMC trial;2018 to 2020) or not enrolled due to operational constraints and hence received standard, non research care. All infants were prospectively followed until inpatient discharge or death. The eKMC trial previously found no important effect of early KMC on all cause neonatal mortality. For this analysis, inpatient mortality rates were compared using a generalised linear model, adjusting for baseline differences in participant characteristics. Prospectively collected data on small and sick newborn care readiness and delivery during the trial period were used to explore how trial participation may have influenced survival. Results A total of 545 neonates were included: 279 enrolled in the trial and 266 not enrolled, predominantly due to the absence of an available caregiver. Baseline characteristics were similar between groups, although differences were seen in twin status, place of birth, and age at admission. Trial participation was associated with an absolute reduction in inpatient mortality of 6.3% (22.6% (63/279) among enrolled versus 28.9% (77/266) among non enrolled) and a relative reduction of 29% (aRR 0.71, 95% CI 0.53 to 0.96). This association varied by season, with no evidence of benefit during the dry season (aRR 0.97, 95% CI 0.60 to 1.58), but a 40% reduction in adjusted mortality risk during the rainy season (aRR 0.60, 95% CI 0.41 to 0.87)(Interaction test: p=0.086). Trial participants had access to laboratory diagnostics and received more intensive clinical monitoring, including higher staffing ratios, continuous pulse oximetry, structured education of carers on neonatal danger signs, and enhanced scrutiny of clinical management compared to neonates receiving routine care. Conclusion Trial participation was associated with a substantial reduction in inpatient mortality, suggesting that participation effects should be considered when designing, interpreting, and reporting neonatal clinical trials in LMIC settings. The association was evident only during the rainy season. The participation effect may have been mediated by increased clinical oversight and monitoring, additional nursing support, and access to diagnostic investigations, all of which should be prioritised within routine care to accelerate progress towards SDG neonatal survival targets.

Transmission-blocking vaccines (TBVs) are a promising strategy to reduce malaria transmission by targeting parasite stages within the mosquito. However, parasite genetic diversity may limit vaccine efficacy. We used next-generation amplicon deep sequencing to identify non-synonymous single nucleotide polymorphisms (SNPs) in Pfs25 from 184 Plasmodium falciparum isolates from Senegal, Tanzania, Ghana, and Burkina Faso. Prioritized SNPs were introduced into P. falciparum via CRISPR-Cas9. For the G116C variant, gametocyte development was evaluated by microscopy and qPCR, and mosquito infectivity was assessed by SMFAs. We identified 26 SNPs, including 24 novel variants. Functional assays showed that the Pfs25 G116C mutation did not affect gametocyte development or exflagellation. SMFA showed no significant differences in oocyst prevalence or intensity between mutant and WT parasites. These findings highlight the importance of integrating genetic surveillance with functional validation to guide the development of effective transmission blocking interventions

Objective To develop and evaluate an automated large language model (LLM)-based framework for conducting meta-analyses of nutrition-related exposures and the risk of breast, ovarian, and uterine cancers. Design We developed MetaFemina, an automated evidence-synthesis pipeline for women's cancers that integrates keyword-based literature retrieval, LLM-assisted evidence extraction, and random-effects meta-analysis. We evaluated its performance against two recently published peer-reviewed meta-analyses and compared exposure-outcome associations across the three cancer types. Data sources PubMed articles identified through keyword-based searches of titles and abstracts. Methods MetaFemina was developed as a web platform that identifies relevant scientific articles, automatically extracts relevant information using LLMs, and synthesizes extracted evidence using random-effects meta-analysis. Additional analyses included assessment of heterogeneity, publication bias, and leave-one-out sensitivity analyses. The platform also provides sample size calculations based on synthesized effect sizes and generates visual summaries and plain-language interpretations. Results Compared with two recent peer-reviewed meta-analyses of folate and vitamin E intake in relation to breast cancer risk, MetaFemina demonstrated high sensitivity (81.82% and 80%, respectively) in identifying eligible studies and additionally retrieved relevant articles that had been missed by manual screening (27 and 13, respectively). Among 226 exposures considered, lutein and beta-carotene were significantly associated with lower risks of breast, ovarian, and uterine cancers. Vitamin D, antioxidants, and soy were significantly associated with lower risks of both breast and ovarian cancers, whereas calcium and folic acid were significantly associated with lower risks of both breast and uterine cancers. In contrast, iron, red meat, and copper were significantly associated with higher risks of both breast and uterine cancers. omega-6 fatty acids showed contrasting associations, being significantly associated with higher breast cancer risk but lower ovarian cancer risk. After restriction to dietary-intake studies, these cross-cancer significant associations remained statistically significant except for copper, which no longer met the two-study threshold for either breast or uterine cancer. Additionally, calcium became significantly associated with lower ovarian cancer risk, resulting in significant negative associations across all three cancer types, while vitamin E became significantly associated with lower breast cancer risk and remained significantly associated with lower ovarian cancer risk. Conclusions MetaFemina demonstrated high sensitivity for identifying relevant scientific literature, extracts key evidence, and performs statistically rigorous automated meta-analyses. The framework may facilitate more rapid evidence synthesis in nutritional epidemiology and may support researchers in study design, hypothesis generation, and interpretation of emerging evidence.

Household environments in low-resource settings can become contaminated with fecal matter from multiple sources, including humans and domestic animals. Identifying the source of fecal contamination is critical for designing targeted interventions to reduce exposure to enteric pathogens, particularly for young children who bear the majority of the enteric disease burden. Using data from 140 households with children enrolled in the ECoMiD cohort study in northwestern coastal Ecuador, we (1) characterized source-specific fecal contamination in samples from household floors and maternal and child hands, and (2) identified animal-related and Water, Sanitation and Hygiene (WASH) conditions associated with the presence and concentrations of these markers. We used five qPCR-based microbial source tracking (MST) markers to detect fecal contamination from avian (GFD), canine (DG37), swine (Pig2Bac), ruminant (Rum2Bac), and human (HF183) sources. Prevalence ratios (PR) and mean differences comparing the presence/absence and concentration, respectively, of MST markers between households with and without each animal-related or WASH condition were estimated using generalized linear models with Poisson and Gaussian distributions. Animal MST markers tracked strongly with several animal-related conditions, whereas associations between the human MST marker and household demographic and WASH conditions were more limited. Animal ownership (PR 1.53; 95% CI: 1.04-2.26) was associated with higher prevalence of animal MST markers on floors. Households reporting animal feces indoors had higher prevalence of animal MST markers on floors (PR 1.84; 95% CI: 1.17-2.89), and higher concentrations of animal MST markers on child hands (mean difference 0.27 gene copies (gc)/m2; 95% CI: 0.12-0.41) and maternal hands (mean difference 0.10 gc/m2; CI: 0.02-0.18). Animal feces left unremoved outside the home were associated with higher prevalence of animal MST markers on maternal hands (PR 2.31; 95% CI: 1.11-4.81). Mothers reporting direct contact with animals had higher concentrations of animal MST markers on their children hands (mean difference 0.12 gc/m2; 95% CI: 0.02-0.21). Higher FECEZ scores, an overall metric for animal exposure, were associated with higher prevalence of animal MST markers on maternal hands (PR 2.94; 95% CI: 1.17-7.40). For human fecal contamination, the presence of E. coli on child hands was associated with higher prevalence of human MST markers on floors (PR 1.30; 95% CI: 1.00-1.68). Our findings reinforce household floors and maternal and child hands as key reservoirs of fecal contamination and point to future potential targets worth exploring for interventions in similar high-burden settings.

Toxicants in the environment can significantly impact physiology. Environmental chemical exposures during early developmental stages disturb normal embryonic development and programming, and dramatically impact long-term health as individuals age. Female and male animals show distinct phenotypes when responding to a given chemical exposure. Here, through the TaRGET II (Toxicant Exposures and Responses by Genomic and Epigenomic Regulators of Transcription) consortium, we systematically explored sex-specific transcriptomic and epigenomic alterations in response to various toxicants, including arsenic (As), lead (Pb), tributyltin (TBT), bisphenol A (BPA), di(2-ethylhexyl) phthalate (DEHP), dioxin (TCDD), and fine particulate matter (PM2.5), across three time points in mice exposed two weeks prior to conception through gestation and lactation. After being exposed to toxicants during the embryonic and early postnatal developmental stages, 1,025 omics datasets were generated from the liver and analyzed across three mouse life stages. We discovered a significant sex-biased molecular response to distinct exposures in the liver at both the transcriptomic and epigenetic levels, showing dynamic changes across mouse development and aging. The perturbed pathways and transcription factors in response to different chemical exposures in both sexes were further evaluated to measure the sex-specific impact of each toxic exposure in the liver. Overall, this study presents the most detailed investigation of sex-specific molecular signatures under the influence of developmental exposures to toxic substances.

Pneumococcal vaccination of older adults is primarily guided by age and clinical eligibility, despite substantial variation in individual risk of severe pneumonia. Here, we used longitudinal electronic health records from 787,538 adults aged [&ge;]65 years to evaluate the real-world effectiveness of the 20-valent pneumococcal conjugate vaccine (PCV20) and quantify clinical benefit according to baseline risk of pneumonia hospitalization. We developed and validated a machine-learning model using pre-PCV20 data to estimate individual 12-month hospitalization risk and integrated these predictions into a propensity score matching framework. Overall vaccine effectiveness against pneumonia hospitalization was 16.5% (95% CI, 10.6-22.1), but this population-level estimate masked substantial heterogeneity in clinical benefit. The 60% at lowest predicted risk, characterized by younger age and fewer pulmonary and other chronic conditions, showed no measurable reduction in hospitalization (VE, 3.1%; 95% CI, -14.4 to 18.0) and had an estimated 1-year number needed to vaccinate (NNV) of 7,423, compared with 184 and 115 in the intermediate- and high-risk groups, respectively. These findings suggest that incorporating baseline risk into adult pneumococcal vaccination strategies could enable more targeted and potentially better-timed vaccination.

Caesarean section in Bangladesh reached 51.8% of deliveries in 2025, and elective caesarean, meaning caesarean before labour began, reached 31.6%. Risk models built on national household surveys are increasingly proposed for pointing audit toward places where scheduled surgery is outrunning clinical need, but they are usually validated in ways that flatter them. Using the 2025 Bangladesh Multiple Indicator Cluster Survey, we developed four models on 9,538 women (logistic regression, elastic net, random forest, gradient boosting) and ran the same procedure under three validation designs: random five-fold cross-validation; five-fold cross-validation grouped by sampling cluster; and leave-one-division-out cross-validation. We also tested transfer between the 2019 and 2025 rounds and audited subgroup calibration. No model improved on logistic regression by a margin worth acting on: the area under the receiver operating characteristic curve ranged from 0.724 to 0.736 under cluster-grouped validation, a spread of 0.012. Validation design mattered far more than the algorithm. Grouping folds by sampling cluster changed discrimination by at most 0.0004, this survey contributing a median of 3 eligible women per enumeration area. Withholding a whole division cost 0.044 to 0.060, more than 100 times as much, and still cost 0.033 to 0.056 after the strongest predictor, an outcome-derived district rate, was removed from every model. A model fitted to 2019 data lost 0.083 when applied to 2025, and the two rounds agreed only moderately on which predictors mattered (Spearman rank correlation 0.61). Calibration held in every wealth quintile, both residence categories and seven of eight divisions; Sylhet was the exception. Elective caesarean is predictable from routine survey items, but that predictability is local. Cross-validation, including cluster-aware cross-validation, does not measure what a model would do in a district it has never seen; a geographic holdout is the cheapest design that does.

Background In sub-Saharan Africa, women are navigating overlapping burdens of undernutrition and rising overweight/obesity, often within fragile health system and rapidly changing food environments. In the DRC, theses tensions may be intensified by rapid urbanization, socioeconomic disparities, insecurity and shifting lifestyles. Despite those changes, national level evidence on who is the most affected by excess weight and why remains scarce. This study assessed the determinant of overweight and obesity among Congolese women of reproductive age, aiming to highlight the social and geographic inequalities. Methods We analysed nationally representative data from the 2023 DHS. The analysis included 10,740 non-pregnant women aged 15-49 years with valid anthropometric measurements. Overweight/obesity was defined as BMI [&ge;] 25 Kg/m2. We examined a broad range of potential associated factors, including province, residence, socioeconomic status, household structure, education level, marital status, occupation, dietary diversity score, healthy diet related indicators, media exposure, internet use and health service utilisation. Weighted analyses accounted for the DHS sampling design. Variables associated at p value < 0.20 were retained for multivariable modelling. Multicollinearity was assed via adjusted GVIFs. Four hierarchical weighted logistic regression were built; the fully adjusted model guided final interpretation. Results Nearly on five women of reproductive age (19.5%) lived overweight or obesity. However, this burden was not evenly distributed. Women from Kongo Central and Tshuapa exhibited significantly lower odds, while those in Bas-Uele, Nord-Kivu, Sud-Kivu and Maniema were substantially more affected, highlighting spatial inequities. Women living in rural areas had lower odds of overweight/obesity compared with their urban counterparts (aOR=0.6; 95% CI: 0.48-0.79; p<0.001). A pronounced socioecomic gradient was observed. Compared with the poorest households, the likelihood of excess weight increases progressively among women in middle income household (aOR=1.65;95% CI:1.13-2.41), rich households (aOR=2.41; 95%CI:1.62-3.60), and was highest among the richest (aOR=4.19; 95%CI: 2.45-7.16). Larger households appeared protective, with lower odds observed in household of 4-5 members (aOR=0.68; 95%CI:0.5-0.92), 6-7 (aOR=0.72;95% CI: 0.54-0.97) and [&ge;]8 members (aOR=0.69; 95%CI:0.50-0.95) compared with smaller household. Age was the strongest predictor, with risk sharply accelerating after 30 years. Being married or in union was associated with higher odds. Notably, frequent internet use independently predicted overweight/obesity. In contrast, dietary diversity and unhealthy food indicators were not significantly significant in the fully adjusted models. Conclusion Overweight and obesity are rising among Congolese women, but unevenly and unjustly. Urban residence, socioeconomic status, age and digital exposure strongly sharply shape who is the most affected, revealing deep social and geographic inequities. Addressing this growing epidemic requires equity-oriented, province specific actions, alongside stronger primary prevention. Key-word: Overweight-obesity-associated factors, DRCongo, DHS

Background Lower respiratory infections (LRI) remain the leading infectious cause of death in children, and survival once ill is a direct tracer of health-system quality. Whether countries are converging toward the best survival performance achieved within their own region has never been tested at national level. We measured each country's distance to an empirical episode-fatality-ratio (EFR) frontier in 204 countries from 1990 to 2023. Methods For each country and year we computed EFR = LRI deaths/incident episodes using Global Burden of Disease (GBD) 2023 estimates for ages 0-19 years. Deaths span the full 1990-2023 series; episodes are observed for 1990, 2019 and 2023, with intermediate years linearly interpolated. The frontier was the 10th-percentile country EFR within each GBD super-region and year (sensitivity: 5th and 25th percentiles); the gap = EFR_country/EFR_frontier. We classified 33-year gap trajectories into catch-up phenotypes, ranked COVID-window (2019-2023) movers, cross-tabulated gap against avoidable deaths to build a priority list, and benchmarked upper respiratory infections (URI) at three time points as a near-zero-fatality contrast. Findings The median country's gap was 1.86 in 1990, 1.80 in 2019 and 1.86 in 2023; the share of countries more than twice their regional frontier was 44.6% in 1990 and 46.6% in 2023. Of 137 eligible countries, 67 narrowed and 69 widened their gap, with one unchanged. Nineteen countries achieved sustained catch-up, concentrated in North Africa and the Middle East (7) and Latin America (5), with China closing from 2.43 to 0.50, below its regional frontier; 28 countries regressed, led by Central Asia (Uzbekistan x3.5) and including the United States (x2.0). Over the COVID-19 window the median gap peaked at 2.00 in 2021 (+10.8% versus 2019, from unrounded medians) before returning to 1.86. Combining gap with avoidable deaths identifies two distinct policy problems: high-burden, moderate-gap giants (Nigeria 67,490 avoidable deaths, gap 2.4; India 54,109, gap 1.6) and extreme-gap outliers (Uzbekistan, gap 28.6). The Sub-Saharan Africa frontier fell further behind the High-income frontier (ratio 4.2 in 1990, 9.5 in 2023); the median Sub-Saharan African country sits 11.0 times the global 10th-percentile frontier but only 1.78 times its own regional frontier, so within-region benchmarking understates the region's true distance. URI gaps likewise did not converge (median 4.15 to 4.60). Interpretation Convergence toward the survival frontier is not the default national trajectory: over three decades the typical country made no net progress toward the best decile of its own region, and pandemic-era divergence was only partly reversed. National gap trajectories separate system-wide quality shortfalls from extreme outliers warranting audit, and expose a measurement trap in which regions whose frontiers stagnate appear closer to best practice than they are.

Background: Large-scale biobanks have advanced genomic and epidemiologic research, but many rely on infrequent biological sampling and limited digital phenotyping. The Yamanashi Multi-omics Cohort (YMoC) was established to support longitudinal assessment of molecular, clinical, and behavioural changes in a screening-defined cohort of adults at elevated metabolic risk without diagnosed diabetes. Methods: YMoC is a longitudinal cohort of 215 adults aged 30-70 years in Yamanashi Prefecture, Japan, who met prespecified glycaemic eligibility criteria at health check-up, including fasting plasma glucose 100-125 mg/dL (5.6-6.9 mmol/L) and HbA1c <6.5%. Participants underwent three in-person visits over six months. Measurements include 75-g oral glucose tolerance testing with serial sampling, clinical biochemistry, anthropometry, liver elastography, and collection of blood, urine, stool, and saliva for multi-omics profiling. Between visits, participants wore a Fitbit Inspire 3 and completed daily app-based questionnaires using the Taohealth app. Current molecular data include genome-wide single nucleotide polymorphism array genotyping and longitudinal plasma proteomics in a subset. Conclusions: YMoC is designed to evaluate within-person molecular and phenotypic trajectories in a screening-defined metabolic-risk cohort. The cohort provides a dense longitudinal resource linking clinical assessments, biospecimens, omics assays, and digital phenotyping, including analyses of insulin-resistance-related markers such as homeostasis model assessment of insulin resistance (HOMA-IR).