Background:To evaluate the associations of pre-pregnancy body mass index (BMI) and first-trimester remnant cholesterol (RC) level with the risk of large for gestational age (LGA) infants. Methods:A prospective cohort study was conducted in Southeastern China, including 11,319 pregnant women. Logistic regression was used to examine the associations of pre-pregnancy BMI and RC level with LGA. Restricted cubic spline regression was applied to assess the dose-response relationship between RC level and LGA risk. Mediation analysis was performed to evaluate the potential mediation role of gestational diabetes mellitus (GDM) in the associations of pre-pregnancy BMI and RC level with LGA. Results:Compared with the reference groups, LGA risk was significantly higher in women with a pre-pregnancy BMI≥24kg/m2 (odds ratio (OR) = 1.60; 95% CI = 1.31 ~ 1.95) and those in the highest tertile of RC (OR = 2.09; 95% CI = 1.67 ~ 2.61). No significant multiplicative or additive interactions were observed between BMI and RC level on LGA risk. Gestational diabetes mellitus mediated 0.91% (RC) and 1.15% (BMI) of effects. Population-attributable risk estimates indicated that 6.69 and 19.68% of LGA cases could be attributed to high pre-pregnancy BMI and elevated RC levels, respectively. Conclusions:Elevated RC and pre-pregnancy BMI are independent LGA risk factors, with minimal GDM mediation. Managing lipid profiles, particularly RC, is important even in high-BMI women.
Background:Serum sodium and urine output (UO) are routinely monitored indicators of electrolyte homeostasis, renal perfusion, and organ function in sepsis. However, the prognostic relevance of their combined longitudinal patterns remains unclear. Methods:We conducted a retrospective cohort study using the Medical Information Mart for Intensive Care IV database. Group-based multi-trajectory modelling identified combined trajectories of serum sodium and UO across four 24-hour periods during the first 96 hours after intensive care unit admission. Cox regression evaluated associations between trajectory subtypes and 30-day mortality, with subgroup and sensitivity analyses. Results:Among 7127 patients with sepsis, five trajectory subtypes were identified. Subtype 1 was characterised by a mild initial decrease in serum sodium followed by recovery and gradually increasing UO. Compared with subtype 1, subtype 2, characterised by mildly increasing serum sodium and gradually decreasing UO, showed the highest 30-day mortality risk in the fully adjusted model (HR = 1.85; 95% CI = 1.56-2.19, P < 0.001). Higher 30-day mortality was also observed for subtype 3, characterised by relatively stable serum sodium and UO that increased and then decreased (HR = 1.22; 95% CI = 1.03-1.46, P = 0.026); subtype 4, characterised by gradually increasing serum sodium and UO that increased before levelling off (HR = 1.31; 95% CI = 1.10-1.56, P = 0.003); and subtype 5, characterised by gradually decreasing serum sodium and UO that increased before levelling off (HR = 1.53; 95% CI = 1.29-1.82, P < 0.001). Subgroup and sensitivity analyses generally supported these findings. Conclusions:Five combined serum sodium and UO trajectory subtypes were identified in sepsis. Subtype 1 was associated with a favourable prognosis, whereas subtypes 2 and 5 carried the highest mortality risks. Early combined trajectories of serum sodium and UO may support prognostic risk stratification, although causal inferences cannot be drawn from this observational study.
Despite growing calls to decolonise global health, many research capacity strengthening initiatives in low- and middle-income countries (LMICs) remain externally driven, short-term, and focused primarily on individual training rather than sustainable institutional ecosystems. Drawing on experiences from the RESPIRE collaboration across South and Southeast Asia, we reflect on key lessons and enabling mechanisms for operationalising equitable global health research partnerships through the ESSENCE. RESPIRE illustrates how capacity strengthening can move beyond transactional partnerships towards locally anchored, sustainable, and LMIC-led research ecosystems grounded in local leadership, regional peer learning, governance, mentorship, and community engagement. These experiences offer practical lessons for funders, institutions, and partnerships seeking to strengthen equitable research capacity in LMICs.
Traditional secondary meta-analysis workflows are highly labour-intensive, time-consuming, and difficult to update in real time. Currently, there is a lack of comprehensive artificial intelligence frameworks capable of automating the entire meta-analysis workflow, including literature screening, data extraction, and quality assessment. Furthermore, a large-scale structured database for systematically analysing the global landscape of published meta-analyses remains unavailable. In this viewpoint, we aimed to evaluate the feasibility of large language models in automating meta-analysis workflows and develop the Meta-Analysis Screening, Transformation and Evaluation Review Agent (MASTER) agent; establish a large-scale Unified Meta-Analysis Repository (UMAR) and perform an exploratory panoramic analysis of the current evidence ecosystem; and develop an Agent-based Secondary Meta-analysis Platform (ASAP), integrating these capabilities. We subsequently applied the agent to process 311,751 meta-analysis records to establish the UMAR database. Building upon these resources, we developed the ASAP platform to support multimodal, automated meta-analysis workflows. In benchmark evaluations, the MASTER agent demonstrated high accuracy and stability in performing core automated meta-analysis tasks. The ASAP platform enabled automated literature retrieval, quality assessment, data extraction, and visualisation generation through predefined workflows. Here, we provide an initial exploration of the technical feasibility and scalability of artificial intelligence-driven automated meta-analysis.
Background:Fine particulate matter (PM2.5) air pollution is a major environmental health concern and has been associated with adverse respiratory outcomes, particularly among older adults. Evidence regarding the short-term respiratory effects of PM2.5 in communities near newly industrialising areas in Thailand remains limited. We aimed to examine the short-term association between daily ambient PM2.5 concentrations and respiratory healthcare utilisation among older adults living near a newly established industrial area in central Thailand. Methods:We conducted a time-series study among residents aged ≥60 years living within a 5 km radius of an industrial area in central Thailand from November 2023 to March 2024. Daily respiratory healthcare visits (ICD-10 codes J00-J99) were obtained from electronic medical records of the local secondary-level hospital. We obtained daily PM2.5 concentrations and meteorological data from the nearest governmental air-quality monitoring station. Associations between PM2.5 exposure and respiratory visits were analysed using negative binomial regression models and expressed as incidence rate ratios (IRRs) per 10 μg/m3 increase in PM2.5. We used single-lag and moving-average models to assess delayed effects, adjusting for temperature, relative humidity, wind speed, day of the week, and temporal trends. Results:A total of 924 respiratory healthcare visits were recorded during the study period, with a mean of 6.37 visits per day. The mean daily PM2.5 concentration was 42.43 μg/m3 (standard deviation = 15.12), substantially exceeding the World Health Organization guideline. Positive associations between PM2.5 and respiratory visits were observed across several lag days, with the largest effect estimate at lag 4. A 10 μg/m3 increase in PM2.5 at lag 4 was associated with a 5.5% increase in respiratory healthcare visits (IRR = 1.055, 95% confidence interval = 0.995-1.119), although this association did not reach statistical significance. Subgroup analyses showed numerically larger effect estimates among females and individuals aged 60-69 years; however, interaction tests were not statistically significant. Conclusions:Short-term exposure to ambient PM2.5 showed a positive but non-significant association with respiratory healthcare utilisation among older adults living near a newly industrialising area. Continued efforts to improve air quality and protect vulnerable populations may help reduce pollution-related respiratory health burdens.
Background:Diabetic retinopathy (DR) and Alzheimer disease (AD) share metabolic and vascular dysfunctions, but the extent to which they reflect overlapping genetic susceptibility and neurovascular-metabolic regulatory pathways remains unclear. We combined multi-omics analyses with population-based data to examine the genetic convergence, cellular pathways, and longitudinal association between DR and AD. Methods:We performed a two-sample Mendelian randomisation (MR) to estimate the association between genetically predicted DR liability and AD risk. We used Bayesian colocalisation analysis to identify shared genomic loci, and summary-data-based MR (SMR) to detect expression-mediated genes jointly associated with DR and AD. We analysed single-cell RNA sequencing data to characterise shared cellular features and related biological pathways. We also conducted an MR-based mediation analysis to explore whether lipid-related, metabolic, or inflammatory traits mediated the observed DR-AD association, and a longitudinal analysis of the UK Biobank cohort to assess the association between DR and incident AD. Results:With the MR analysis, we found that genetically predicted liability to DR was associated with a modest increase in AD risk. Colocalisation analysis supported a shared genetic signal. We identified three genes with shared expression-mediated associations across DR and AD through SMR. Functional enrichment analyses revealed partially overlapping neurovascular and metabolic pathways. Using MR-based mediation analysis, we found no significant intermediary traits linking DR and AD. Findings from the UK Biobank cohort were directionally consistent with the genetic analyses. Conclusions:Genetic liability to DR is associated with an increased risk of AD and is accompanied by shared expression-mediated effects and convergent neurovascular-metabolic pathways. These findings support the possibility that DR may serve as a clinically accessible indicator of increased neurodegenerative vulnerability.
Background:Tobacco use and second-hand smoke (SHS) exposure remain highly prevalent in Pacific Island nations, but evidence on their health consequences is limited. We aim to describe the prevalence of smoking and SHS exposure in Tuvalu, their associations with body measurements and sleep-related outcomes, and the heterogeneity by island of residence and age group. Methods:COMmunity-based Behaviour and Attitude surveys were conducted in Tuvalu between 2020 and 2025 among 4,066 participants from Funafuti and outer islands. Smoking status was assessed in all survey years, and SHS exposure was assessed in 2022, 2023, and 2025. Body composition (body mass index (BMI), waist and neck circumference) and obstructive sleep apnoea (OSA)-related outcomes in STOP-Bang scores were measured. We assessed the associations with multivariable linear and logistic regression, with stratified analyses by age group and island of residence. Results:Overall, 26.1% of participants were people who currently smoke and 60.7% reported SHS exposure. The mean BMI was 32.1 kg/m2, and 23.7% of participants had a STOP-Bang score ≥3. Current smoking (odds ratio (OR) = 1.80; 95% confidence interval (CI) = 1.30, 2.48) and SHS exposure (OR = 2.15; 95% CI = 1.54, 3.02) were associated with obesity, higher STOP-Bang scores and increased odds of STOP-Bang ≥3, which varied by island of residence. Conclusions:In Tuvalu, both active smoking and SHS exposure were associated with obesity and OSA-related outcomes, with variation by island of residence. These findings indicate the importance of strengthening the implementation and enforcement of comprehensive tobacco control for sleep health and non-communicable disease prevention in Pacific Island populations.
Background:Childhood acute respiratory symptoms (ARSs) remain an important public health concern in South Asia, but meteorological associations may not be transferable across climatically diverse settings. Studies that rely on pooled regional estimates or single exposure metrics may therefore obscure meaningful heterogeneity. We examined whether associations of childhood ARSs with temperature and vapour pressure deficit (VPD) differed across macroclimatic regimes in four South Asian countries. Methods:We analysed Demographic and Health Survey data from India, Bangladesh, Nepal, and Timor-Leste, initially comprising 244,437 children aged <5 years aggregated into 33,407 survey cluster-month units. Childhood ARS was defined using a harmonised symptom-based measure based on caregiver-reported fast breathing and chest-related breathing difficulty during the preceding two weeks. Monthly temperature and VPD were assigned from ERA5 reanalysis data. We estimated the associations within country-macroclimate strata using mixed-effects binomial logistic regression models adjusted for demographic, socioeconomic, and household environmental covariates. Results:Meteorological associations with childhood ARS varied substantially across climatic regimes. Temperature-related associations were heterogeneous in both direction and magnitude across strata. By contrast, the clearest and most robust inverse association was observed for VPD in India's arid macroclimate (odds ratio (OR) = 0.56; 95% confidence interval (CI) = 0.44, 0.71). In humid tropical settings, associations for both temperature and VPD were largely null. In India's arid macroclimate, comparing the highest vs lowest VPD tertile corresponded to a risk difference of -1.28 percentage points (95% CI = -2.14, -0.71), equivalent to approximately 13 fewer ARS cases per 1000 children surveyed. Conclusions:Meteorological associations with childhood ARS were strongly context-dependent and should not be assumed to be uniform across climatic regimes. In this multicountry analysis, VPD showed the clearest association in India's arid macroclimate, whereas temperature-related associations were more heterogeneous across settings. These findings highlight limitations of pooled regional interpretations and support climate-stratified approaches to meteorological risk assessment in child health surveillance. Keywords:childhood acute respiratory symptoms; South Asia; climatic heterogeneity; vapour pressure deficit; temperature; child health surveillance.
Background:Neck pain (NP) is a leading musculoskeletal disorder globally. Posture management is crucial for its prevention; however, population-level evidence quantifying the associated factors in real-world settings remains limited. We aimed to identify and quantify threshold effects of key factors related to posture management associated with NP among Chinese adults. Methods:We conducted a multicentre, cross-sectional study across six Chinese cities. We collected data via face-to-face interviews using a questionnaire covering demographics, occupational factors, electronic device use, sleep, transportation, and exercise. Multivariable logistic regression identified factors associated with NP. We used restricted cubic splines to model nonlinear relationships, and applied the Akaike information criterion to determine dichotomisation cutoffs for continuous variables. Propensity score matching assessed the robustness of these associations, and subgroup analyses by sex and age assessed heterogeneity. Results:We included a total of 6,969 adults (≥18 years), comprising 2,662 (38.2%) with NP and 4,307 (61.8%) without. Identified associated factors included: computer use time for work ≥2 hours/day (odds ratio (OR) = 1.39; 95% confidence interval (CI) = 1.16-1.67, P < 0.001), smartphone use time for work ≥3 hours/day (OR = 1.21; 95% CI = 1.03-1.42, P = 0.022), smartphone screen height below horizontal eye level (OR = 1.16; 95% CI = 1.00-1.34, P = 0.043), and firm mattress (OR = 1.19; 95% CI = 1.04-1.37, P = 0.012) were associated with increased odds of NP. Sleeping time ≥7 hours/day (OR = 0.79; 95% CI = 0.69-0.89, P < 0.001), supine sleeping (OR = 0.87; 95% CI = 0.76-0.99, P = 0.039) and walking as the primary mode of transportation (OR = 0.80, 95% CI = 0.70-0.91, P < 0.001) were associated with decreased odds of NP. Conclusions:This study identified and quantified threshold effects of key factors associated with NP among Chinese adults, including electronic device use, sleep habits, and commuting patterns. These quantified thresholds offer actionable benchmarks for posture management of NP in clinical practice and public health interventions. Registration:Chinese Clinical Trial Registry: ChiCTR2400093567.
Development assistance has historically supported major gains in health and health-system development in sub-Saharan Africa, but recent reductions in development assistance have intensified financing and service-delivery pressures across the region. As governments seek more durable and domestically sustained strategies, the private health sector may play a larger role in expanding financing, specialised care, innovation, workforce retention, and public-private partnerships. However, private sector expansion alone is not sufficient and may worsen inequities if it remains disconnected from national financing frameworks, accreditation systems, quality standards, and public accountability. Here, we argue that private providers should be incorporated into well-regulated mixed health systems that align commercial incentives with universal health coverage, equity, and public health goals. Experiences from Ghana and Kenya have shown that integration depends on timely reimbursement, efficient accreditation, and deliberate efforts to reach underserved populations. Private-sector engagement should therefore complement, not substitute for, strong public health systems.
Background:Recent years have shown an unexpected increase in infant mortality in Spain, raising concerns about maternal, socioeconomic, and healthcare factors. Methods:We performed a retrospective analysis of national and European infant mortality data from 2009 to 2024. Joinpoint regression was used to detect trend changes. Socioeconomic, maternal age, and healthcare access factors were analysed to identify potential contributing elements. Results:The analysis identified a significant upward trend in infant mortality from 2019 onwards. Delayed maternal age, socioeconomic disparities, and reduced healthcare system satisfaction appear associated with this increase. Cross-country comparison indicates that these trends are not unique to Spain. Conclusions:The rise in infant mortality in Spain and Europe may have multifactorial causes, including delayed motherhood, post-pandemic healthcare strain, and socioeconomic inequities. Public health policies should urgently address these factors to prevent further increases.
Background:Accurate respiratory rate (RR) assessment is essential for pneumonia identification under World Health Organization Integrated Management of Childhood Illness (IMCI) guidelines; however, manual RR counting is often inaccurate and difficult in routine care. Automated RR counters have been developed to address these challenges, but evidence on their diagnostic performance and implementation in low- and middle-income countries (LMICs) remains limited. This systematic review evaluated the accuracy, usability, acceptability and time efficiency of automated RR counters for RR assessment to support identifying pneumonia in children aged 0-59 months in LMICs. Methods:We searched MEDLINE, EMBASE, Web of Science, and Scopus for studies published between 1 January 2014 and 15 July 2025. Studies conducted in LMICs assessing automated RR counters in children aged 0-59 months were eligible, including quantitative, qualitative, and mixed-methods designs. Study quality was assessed using the Joanna Briggs Institute appraisal tools. Quantitative findings were synthesised narratively, and qualitative findings were analysed thematically. Results:Fourteen studies from seven LMICs were included. Two automated RR counters - Masimo Rad-G and ChARM - were evaluated. Masimo Rad-G showed variable performance across studies (sensitivity = 75.9%-95.4%; specificity = 93.8%-98.3%; kappa = 0.55-0.85, n = 3), while ChARM demonstrated high diagnostic performance (sensitivity = 95.8%; specificity = 93.5%; kappa = 0.74-0.86, n = 2). Usability studies reported generally positive user experiences, though performance was affected by child movement, adherence to measurement procedures, and device design. Health workers and caregivers perceived automated tools as more reliable than manual counting, with visual indicators improving confidence in clinical decisions. Reported challenges included battery life, maintenance, workflow disruption, and the need for continuous training and supervision. Conclusions:Although the available evidence remains limited, automated RR counters show promise for RR assessment in LMIC settings to support pneumonia identification. Future studies are needed to confirm their effectiveness and implementation feasibility across diverse routine-care settings. Successful adoption is likely to depend on adequate training, device optimisation, and integration into existing health-system workflows. Registration:PROSPERO: CRD420251080564.
Background:Diabetes mellitus is recognised as a risk factor for Parkinson's disease (PD); however, comparative evidence regarding PD risk across antidiabetic drug classes remains limited and inconsistent. We aimed to compare the risk of PD across different antidiabetic classes, with stratified analyses by age, sex, and cardiovascular disease (CVD) status. Methods:We searched the Cochrane Library, Embase, and PubMed until August 2025 for studies assessing the association between antidiabetic drugs and PD incidence. We performed a Bayesian network meta-analysis, estimating effect sizes as risk ratios with 95% credible intervals. We performed prespecified subgroup analyses according to age, sex, and CVD status. Results:We included nine observational cohort studies, totalling 712 287 patients. No antidiabetic class demonstrated a statistically significant difference in PD risk. Rank probability analyses suggested that sodium-glucose co-transporter-2 inhibitors (SGLT2i) tended to rank lowest in PD risk among older adults (≥75 years), while glucagon-like peptide-1 receptor agonist (GLP-1RA) ranked lowest in patients aged <75 years. In patients with CVD, metformin showed relatively higher-ranking probabilities for PD risk compared with SGLT2i. In contrast, metformin, sulfonylureas, and α-glucosidase inhibitors were consistently associated with higher ranking probabilities for PD risk compared to newer agents. Conclusions:Our analysis suggests that antidiabetic drugs may exert effects beyond glycaemic control and could influence neurodegenerative risk. Furthermore, SGLT2i and GLP-1RA were consistently associated with lower PD risk, suggesting potential neuroprotective effects. While our results indicate the potential importance of antidiabetic drug selection in patients at risk for neurodegenerative diseases, further large-scale, controlled studies should validate these associations and clarify potential mechanisms. Registration:PROSPERO: CRD420251130232.
Background:Congenital anomalies (CAs) are structural or functional changes occurring during intrauterine life. The World Health Organization data indicate that about 295,000 babies die within the first four weeks of birth due to CAs every year. It has been estimated that approximately 94% of severe CAs occur in low- and middle-income and low-income countries. While the use of a national congenital anomaly registry (CAR) can help improve healthcare quality, access, and planning for families and children born with CAs, few countries report using such a system. We aimed to evaluate the correlation of health and economic indicators with the existence of national CARs. Methods:We compiled data on individual countries' reported CAR status from regional networks, the International Clearinghouse for Birth Defects Surveillance and Research, the Modell database, and a literature search. We classified countries according to the reported CAR status into those that reported having a national CAR with or without regional CAR, only a regional CAR, and no CAR data available. Using the Kruskal-Wallis test, we analysed whether a country's CAR status was correlated with health and economic data from UNICEF and the World Bank. Results:Of the 202 countries in our sample, 30 reported having a national CAR, 19 only a regional CAR, and 153 no CAR. Country income group-level analysis showed that 35.4% of high-income, 13.2% of upper middle-income, and 0% of low- and middle-income, and 0% low-income countries were reported to have national CARs. Countries lacking a national CAR tended to have a lower gross domestic product (P < 0.001), increased infant mortality rates (P < 0.001), and lower birth registration rates (P < 0.001). Conclusions:While the importance of CARs for improving global health is widely recognised, most LMICs and LICs still do not report having a national CAR. Our study suggests that countries without CARs face greater economic and health systems challenges. Collaborations to develop national CARs need to consider the impact of these wider economic and health systems challenges.
Background:The global burden of neuropsychiatric disorders has been increasing rapidly. Folate has been studied in the context of these disorders due to its role in cellular methylation capacity, which is crucial for normal neuronal gene expression and neurotransmitter syntheses. Epidemiological evidence linking folate and neuropsychiatric disorders is growing, yet inconclusive. Methods:We searched MEDLINE, Embase, CINAHL, the Cochrane Library, and the Database of Abstracts of Reviews of Effects from inception to February 2024 for systematic reviews and meta-analyses investigating the associations between folate exposure and any neuropsychiatric disorders. Two independent reviewers screened the syntheses in two stages and extracted relevant data. Evidence was categorised into unique associations (unique exposure measure - unique outcome - unique setting). We identified evidence for each category of unique associations. We evaluated the risk of bias of all included syntheses using ROBIS and assessed the credibility of evidence using predefined criteria. Results:From a total of 76 syntheses, we identified 44 unique associations from meta-analyses and 18 unique associations from qualitative syntheses across 14 outcome categories. Most of the reviews consisted of case-control studies or cross-sectional studies, and most were at high risk of bias. We identified two associations at a suggestive level of credibility: folic acid supplementation during or before pregnancy was associated with a reduced risk of perinatal depression, while prenatal maternal folic acid use was associated with a reduced risk of autism spectrum disorder in offspring. Seven associations were downgraded to weak due to unavailable data. Other associations were at a weak level of credibility due to insufficient statistical power. Conclusions:The available evidence on the relationship between folate status and neuropsychiatric disorders primarily comprised data from observational studies, limiting causal inference on folate exposure and the risk of onset or progression of neuropsychiatric disorders. Prospective studies and sex-stratified analyses could add to the evolving knowledge on this topic. Registration:PROSPERO: CRD42021265041.
Following the 2014-2016 West Africa Ebola epidemic, the US expanded funding for global health security (GHS) to strengthen outbreak prevention, detection, and response capacity across countries. In this viewpoint, we offer an illustrative comparison between one narrow category of economic benefit to the US - avoided losses in merchandise exports - and US GHS funding directed to the region between 2016 and 2023. Using a transparent accounting identity, we compared US export losses plausibly averted through the local containment of ten Ebola outbreaks during this period against estimated regional GHS appropriations of USD 2.52 billion, applying the 2014 losses as a benchmark and a range of scenarios to reflect uncertainty in the scale of disruption averted. Under the benchmark scenario, each USD of funding corresponded to approximately USD 4.64 in avoided export-related losses. This scoping exercise is intended to convey the order of magnitude of potential returns, rather than a measured economic return or causal attribution, and it deliberately excludes broader benefits. Even through this narrow trade-based lens, the findings suggest that the economic value of containing outbreaks abroad may be large enough to warrant consideration in U.S. budget discussions.
The Nipah virus (NiV) infection is a highly fatal zoonotic disease with pandemic potential which has led to recurrent outbreaks in Bangladesh and India. While transmission pathways, including contaminated date palm sap and human-to-human spread, are increasingly identified, significant uncertainties remain. With no approved therapeutics or vaccines, prevention depends on addressing ecological and behavioural drivers of transmission. This viewpoint draws on selected evidence from NiV outbreaks and response to other zoonotic disease epidemics, such as Ebola, rabies, and the Marburg virus disease, we seek to foster discussion on why community engagement could be central to NiV prevention and preparedness. We highlight the relevance of community engagement through a spectrum of its intensity, which distinguishes between community-oriented, community-based, community-managed, and community-owned approaches. Adapting an existing model, we discuss how community engagement principles can be applied to tackle recurring NiV outbreaks in Bangladesh and India. By aligning interventions with sociocultural realities, community engagement can improve acceptability, enhance early detection, strengthen outbreak response, and support preparedness for future vaccine and therapeutic research. However, evidence specific to NiV remains limited and lessons from other diseases should be applied judiciously. In the absence of medical countermeasures, participatory, locally grounded approaches offer a sustainable pathway to reduce recurrent outbreaks and prevent future spillover events.
Background:The rapid development of China's civil aviation industry has resulted in a greater impact of aircraft emissions on the public health of residents living near airports. Despite attention given to aviation-related environmental issues, research on the health effects of aircraft-related CO, NO2, and SO2 emissions remains limited. We aimed to fill this gap by examining the health impacts of these pollutants on populations surrounding airports in China. Methods:We collected basic flight takeoff and landing information from the Civil Aviation Administration of China and calculated the NO2, CO, and SO2 concentrations at each airport using the Gaussian diffusion model. We also calculated the premature deaths caused by NO2, CO, and SO2 emissions at each airport using the Global Mortality Model and population data near the airports. Results:In our sample, CO, NO2, and SO2 emissions were associated with a higher attributable mortality burden in men than in women, and a greater burden is observed among older age groups. Among the three pollutants, CO accounts for the largest number of respiratory disease deaths. Lastly, we observed the highest number of attributable deaths in 2019. Conclusions:Our findings give new insights into the relationship between aircraft pollutant emissions and health outcomes in China, and thus provides a valuable reference for future research and policy formulation on how aviation impacts public health.
