The Follow-up Longitudinal Observational study on Risk factors and Health in Adults (FLORA) is a prospective cohort established in Guangzhou, China, in 2008 to investigate the impact of rapid urbanization, environmental transitions, and macrosocial changes on non-communicable diseases (NCDs) in working-age and older adults. The cohort comprises 7,855 participants aged 19–83 years at baseline, drawn from the city’s annual mandatory health examination system for civil servants. Followup integrates passive annual electronic health record linkage with active questionnaire surveys, covering a period that spans three major pandemics (H1N1, H7N9, COVID-19) and key national environmental policies. FLORA also includes a biobank for future mechanistic research. The cohort provides a unique platform to examine how macrolevel societal transformations interact with individual-level risk factors in shaping NCD trajectories in a dynamic megacity setting.
Chemical intolerance (CI), in clinical settings often referred to as Multiple chemical sensitivity (MCS), is a condition characterized by adverse reactions to low-level chemical exposures considered non-harmful for the general population. Here we present results from a multiple case-study where we aimed to evaluate the effects of a novel exposure-based intervention for alleviating CI symptoms. Five women underwent repeated, well-controlled exposure to a symptom-eliciting stimulus (n-butanol) in a laboratory setting across five weeks. The main outcome included ratings of symptom intensity following exposure. The results showed consistent reductions in ratings of symptom intensity pre to post intervention, indicating increased tolerance. Further, effects persisted at the six-month follow-up. Treatment adherence was high among all participants. These findings suggest that well-controlled and individualized exposure may be a viable treatment avenue for CI, which is a prevalent condition with limited or no treatment alternatives. Study limitations include the restricted generalizability following a multiple case-study and the limited scalability of the treatment setting.
Background Outdoor particulate air pollution is classified as causing lung cancer, but evidence on specific pollutants and exposure timing remains limited. Methods 22,294 participants in the population-based Malmö Diet and Cancer cohort, were enrolled between 1991 and 1996 and followed until 2016. Incident lung cancer cases were identified through national registers. Annual residential exposure to PM2.5, PM10, black carbon (BC), and nitrogen oxides (NOx) was estimated using high-resolution dispersion models and assigned based on residential history. Time-dependent Cox regression models with age as the time scale were used to estimate hazard ratios (HRs) and confidence intervals (CIs) for lung cancer incidence for exposure at baseline (1990–1994), the five years preceding diagnosis or censoring (lag 1–5), and the 6–10 years prior (lag 6–10). Models were progressively adjusted for smoking (status, intensity, duration), environmental tobacco smoke, employment, occupation, education, physical activity, cohabitation, and area-level socioeconomic status. Results During 325,966 person-years, 499 participants developed lung cancer. In models adjusted for age, sex, and calendar time, positive associations were observed for PM2.5, PM10, BC and NOx. Adjustment for smoking substantially attenuated the estimates leading to imprecise and not statistically significant associations. For example, the HR for PM2.5 (lag 1–5 years) was 1.03 (95% CI: 0.48–2.19) per 5 µg/m³, PM10 (lag 1–5 years) was 1.21 (95% CI: 0.51–2.89) per 10 µg/m³, and for BC (lag 1–5 years) was 1.10 (95% CI: 0.67–1.80) per 0.5 µg/m³, while associations with NOx were close to null. Discussion and conclusion We observed suggestive but imprecise associations between long-term PM exposure and lung cancer incidence. The attenuation after adjustment for smoking highlights the importance of careful confounder control. Overall, findings do not provide strong evidence of an independent association in this low-exposure setting and should be interpreted cautiously.
Asthma and air pollution are major public health concerns that exhibit spatial variation across U.S. urban centers; however, their spatial co-occurrence remains underexplored. This study examined the geographic overlap of asthma prevalence and air pollutants (NO2, SO2 and aerosol optical depth [AOD]) across the eight most populous U.S. metropolitan areas. Zip code tabulation area (ZCTA)-level asthma prevalence estimates from the 2024-release Centers for Disease Control and Prevention PLACES dataset were combined with satellite-derived pollutant data from Sentinel-5P and the Moderate Resolution Imaging Spectroradiometer (MODIS). Hotspot comparison analysis was used to identify areas of compounded risk, defined as overlapping asthma and pollutant hotspots significant at the 95% and 99% confidence levels. Multivariable logistic regression models were then applied to examine associations between sociodemographic characteristics and the likelihood of compounded risk. Compounded risk areas were concentrated within urban cores, with overlap ranging from 0.23%–71.53% across pollutants and metropolitan areas. Across adjusted models, every 10-percentage point increase in the proportion of Black residents was associated with 37%–54% higher odds of compounded risk after accounting for neighborhood poverty, while corresponding increases in Asian populations were associated with about 28% higher odds. Lower educational attainment was consistently associated with increased odds across pollutants, whereas higher renter occupancy was associated with increased NO2- and AOD-related risk. These findings highlight areas where asthma burden and pollution spatially coincide, although the cross-sectional nature and focus on spatial co-occurrence limits causal inference. They underscore the role of urban infrastructure and historical segregation in shaping environmental health inequities.
Infants (<1 year) are among the most vulnerable groups during extreme heat. Whereas caregiver dependence contributes to this vulnerability, the role of infants’ thermoregulatory system remains unclear. This study examined the thermoregulatory responses of twenty healthy, term-born infants (3–13 months) during short-term exposure trials in controlled environments at 23 °C and 34 °C, 20% relative humidity. Estimated core temperature, local and mean skin temperatures, heart rate, and whole-body sweat rate (WBSR) were measured. Heat balance components (dry heat loss, wet heat loss, heat storage, and metabolic heat production) were calculated to quantify heat strain and heat exchange pathways. Outcomes were compared between trials (paired t-tests). At 34 °C, infants showed higher tympanic (+0.4 °C, p < 0.001) and temporal (+0.4 °C, p < 0.001) temperatures, as well as mean skin temperature (+2.2 °C, p = 0.002) and WBSR (+74.1 g/m2/h, p < 0.001) compared to 23 °C. The primary heat exchange pathway differed between trials; dry heat loss constituted 72% of total heat loss (defined as the sum of dry and wet heat loss) at 23 °C but only 11% at 34 °C. Overall heat storage did not differ between trials (p = 0.844). At 23 °C, heat storage was slightly below zero (95% CI [−1.95, −0.14] W), while at 34 °C it was not significantly different from zero (95% CI [−2.47, 0.14] W). Age was related to wet heat loss at 34 °C, with older infants exhibiting higher rates (β = 6.4; 95% CI [2.2, 10.3]). Overall, infants showed no net heat storage over the 60-min exposure at 34 °C, 20% relative humidity, and relied primarily on wet heat loss for heat dissipation. However, over-reliance on evaporative cooling may become dangerous when sweating is restricted by high relative humidity or clothing, emphasizing the importance of facilitating adequate sweat evaporation and hydration in infants exposed to heat.
Background: The incidence of legionellosis has increased in Spain in recent years, potentially influenced by climate-related changes that favour Legionella pneumophila proliferation. Aim: The main aim of this study was to evaluate whether extreme meteorological events are associated with increased sporadic legionellosis incidence. Additional objectives included examining the short-term association across increasing percentiles of each meteorological variable and describing the spatiotemporal distribution of sporadic cases in Spain from 2011 to 2023. Methods: Sporadic Legionnaires’ disease (LD) cases reported to the National Epidemiological Surveillance Network (RENAVE) between 2011 and 2023 were included. Meteorological data on daily mean temperature, cumulative precipitation, mean relative humidity and maximum wind speed from the Spanish State Meteorological Agency (AEMET) stations were aggregated by meteorological warning areas. A generalised linear mixed-effects model was applied in a sensitivity analysis to examine associations between exceeding percentile thresholds (p5–p95) for each variable and incidence 2–14 days later. A second model evaluated the association between days with extreme events (p95) and subsequent incidence. Results: A significant increase in sporadic LD was observed (p < 0.05), with the highest rates in northeastern Spain. Incidence increased progressively with higher percentiles of temperature, precipitation and humidity, while wind percentiles showed an inverse pattern. Days exceeding the 95th percentile of temperature, precipitation and humidity were associated with higher incidence; extreme wind showed no significant effect. Conclusions: Extreme temperature, precipitation and humidity are associated with short-term increases in sporadic LD. Incorporating meteorological indicators into surveillance could improve early warning and support public health interventions under changing climatic conditions.
Phthalates have been linked to higher mortality, but evidence on their relationship with epigenetic aging remains limited, particularly among older adults. We investigated associations between urinary phthalate metabolites and DNA methylation (DNAm)-derived epigenetic age acceleration (EAA) and examined EAA as a potential mediator for the phthalate-mortality association. We analyzed 611 U.S. adults aged ≥ 50 years without baseline cardiovascular diseases (CVD) or cancer diagnosis from the 1999–2002 U.S. National Health and Nutrition Examination Survey (NHANES), followed for mortality through 2019. Baseline urinary concentrations of four phthalate metabolites and EAA derived from four DNAm clocks were analyzed using survey-weighted linear regression, Bayesian Kernel Machine Regression, and quantile-based g-computation for individual and mixture effects. Higher monobenzyl phthalate (MBzP) was associated with accelerated HannumAge (0.60 years per log-unit increase) and was positively associated with all-cause, cancer, and CVD mortality. Mixture analyses suggest MBzP as the primary contributor to accelerated HannumAge, PhenoAge, and GrimAge, despite no significant overall mixture effects. Mediation analyses indicated that EAA partially explained these associations, with the largest proportion mediated for cancer mortality (3.9%-9.2% across clocks). These findings suggest that among older U.S. adults, urinary MBzP was associated with accelerated epigenetic aging, which partially mediated the MBzP-mortality association, highlighting the need to reduce phthalate exposure and supporting DNAm clocks as sensitive biomarkers of environmental toxicity.
This study examines how ground-level ozone (O3) exposure affects mortality in Shanghai (2013–2018), and how temperature modify this relationship in subtropical climate. Using a generalized additive model, we found: (1) A significant non-linear O3-mortality association, with risks rising sharply above 42.1 μg/m3 for cardiovascular diseases; (2) The estimated effects of O3 on mortality varied across different lag days, peaking on lag03; (3) Respiratory mortality most sensitive to O3 exposure compared with total non-accidental or cardiovascular mortality; (4) Higher vulnerability among females, adults ≥60 years, and those with low-education; and (5) Consistent effect modification by temperature, both low- and high-temperature strata have elevated O3-related mortality risks across all cause-specific and demographic subgroups. For temperatures below the 25th, between 25th and 75th, and above the 75th percentiles, a 10 μg/m3 O3 increase was associated with 0.97% (95% CI: 0.64–1.31%), 0.73% (0.30–1.16%), and 0.85% (0.38–1.32%) rises in total non-accidental mortality, respectively. Given ongoing climate change and rising O3 precursor emissions, urgent targeted interventions are needed to protect vulnerable populations from combined O3-temperature exposure.
Particulate matter pollution (PMP) is a significant environmental risk factor for chronic obstructive pulmonary disease (COPD), contributing substantially to the global public health burden. Using data from the Global Burden of Disease Study 2021 (GBD 2021), we quantified COPD-related disability-adjusted life years (DALYs) attributable to ambient particulate matter pollution (APMP) and household air pollution (HAP) from 1990 to 2021. We applied an integrated analytical framework including Joinpoint regression, inequality assessment (SII and CI), decomposition analysis, frontier efficiency evaluation using LOESS regression, and Bayesian age–period–cohort modelling with INLA to assess historical patterns and project future trends. Globally, PMP-attributable COPD DALYs declined over the study period, with substantial heterogeneity across regions and socio-demographic index (SDI) levels. APMP-related burden exhibited a non-linear, inverted U-shaped association with SDI, peaking in middle-SDI regions, whereas the burdens attributable to HAP and total PMP declined consistently with increasing SDI. While COPD burden is generally higher in men, HAP-attributable burden remained disproportionately higher in women in East Asia. Frontier analysis identified countries with substantial excess burden relative to their development level, particularly Papua New Guinea. Projections to 2050 indicate a continued global decline, although regional disparities and uncertainties persist, especially for APMP. These findings highlight distinct epidemiological patterns between ambient and household pollution sources and underscore the need for region-specific and source-targeted interventions to reduce COPD burden and address persistent global health inequalities.
Air pollution is a major environmental risk factor for respiratory health, yet its interaction with seasonality in shaping the upper airway microbiota remains poorly understood. We conducted a longitudinal repeated-measures study to investigate whether seasonality modulates the effects of indoor and outdoor air pollution on the nasal microbiota of healthy adults. Twenty-six participants were sampled weekly for three weeks in winter and three weeks in summer . Microbial composition was characterized using 16S rRNA gene sequencing (124 samples) and whole-genome shotgun sequencing (141 samples). Weekly exposure to indoor total suspended particles (TSP) and outdoor pollutants (particulate matter, black carbon, benzene, and carbon monoxide) was assessed using environmental monitoring data. The nasal microbiota was stable within seasons but differed significantly between seasons, with winter enrichment of Moraxella species, particularly among women with children. Across seasons, higher pollutant levels were negatively associated with relative abundance of commensal taxa, particularly Corynebacterium species. In addition, this study identified significant season-pollutant interactions. For example, in summer, commensal bacteria (e.g., Staphylococcus epidermidis and Cutibacterium granulosum) were found to be negatively associated with particulate matter exposure. Among host factors, sex explained the largest proportion of variance in microbial diversity, while household characteristics contributed additional compositional variability. These findings indicate that the respiratory microbiome varies across seasons and is associated with air pollution, suggesting that both seasonality and environmental exposures can contribute to differences in respiratory microbial communities.
Background: Household air pollution is a major environmental factor that has been linked to adverse cognitive outcomes in older adults. While indoor ventilation has been shown to mitigate these effects, evidence remains limited, particularly regarding ventilation in cooking areas. Methods: Using data from a cross-sectional study of older adults without clinically diagnosed dementia in Kazakhstan, we examined the association between indoor ventilation in cooking and living areas and screen-detected dementia as well as potential interactions, using multivariable regression models. Participants scoring ≥6 on the Quick Dementia Rating System (QDRS) were classified as having screen-detected dementia. Results: Among 578 participants (median age 65, 60% women), 10.4% screened positive for dementia by QDRS. In adjusted models, having a ventilation system in the cooking area was significantly associated with lower odds of QDRS screening-positive dementia compared with not having ventilation (adjusted odds ratio [aOR] 0.41, 95% confidence interval [CI]: 0.21–0.81). Similarly, significantly lower odds of QDRS screening-positive dementia were observed among participants who ventilated the cooking (aOR 0.45, 95% CI: 0.23–0.86) and living (aOR 0.25, 95% CI: 0.08–0.65) areas 2–3 times daily compared to 0–1 ventilation. A significant interaction was found between daily cooking duration and ventilation presence in the cooking area (p=0.009). Conclusion: We found a potentially high burden of dementia in Kazakhstan and observed that better ventilation in cooking and living areas was associated with lower odds of QDRS screening-positive dementia. These findings highlight the potential of improving kitchen ventilation as a public health strategy in the context of dementia.
In 2019, antibiotic resistance posed a significant health threat, leading to 1.27 million deaths worldwide, and the risk expected to persist into the future. Livestock farming is a hotspot for antimicrobial resistance owing to the consumption of antimicrobials and environmental contamination of the surroundings. However, few studies have thoroughly sampled Extended Spectrum (3-Lactamase producing Escherichia coli (ESBL E. coli) throughout the entire process within a single farm, from the initial feed spots to the final fertilizer spots. This study used comprehensive sampling, interviews, antibiotic resistance profiling, and whole-genome sequencing to identify ESBL E. coli hotspots in an integrated teaching farm in Indonesia. All of 134 samples were obtained of livestock and human stool, feed concentrates, water, and livestock fertilizer. E. coli and ESBL E. coli were isolated and characterized using selective media, indole assays, and double-disk synergy testing. DNA from 18 isolates was extracted, sequenced, and analyzed. The investigation discovered ESBL E. coli in 35.1% of the samples (47/134). ESBL E. coli concentrations were highest in poultry fertilizer (7.4 log10 CFU/g), broiler stool (6.7 log10 CFU/g), and broiler feed. Multiple (3-lactam antibiotic resistance genes and extraintestinal pathogenic E. coli virulence genes were identified through genomic analysis, indicating a considerable threat of antibiotic resistance and pathogenicity in this strain. The close genetic relationship between the isolates suggests cross-contamination within the farm environment. Specific hotspots for ESBL E. coli were identified, including broiler stools, poultry fertilizers, and duck stools, based on ESBL E. coli concentration and phylogenetic tree analyses. This study provides new evidence that ESBL E. coli extends beyond livestock stools to feed concentrates and water, while hotspot mapping uncovers hidden hotspots across the farm. The findings advance One Health by guiding stronger biosecurity, waste management, and antimicrobial resistance surveillance in livestock systems.
Background: The association between fine particulate matter (PM2.5) chemical constituents and blood lipid levels remains unclear. This longitudinal study, leveraging data from a comprehensive national survey across 31 provinces in mainland China, aimed to assess the associations between exposure to PM2.5 constituents and blood lipid metabolism. Methods: Utilizing data from the China National Stroke Screening Survey (CNSSS), we included 292,754 participants accounting for 683,759 visits recorded between 2013 and 2019. To investigate the longitudinal relationship between PM2.5, its five constituents (ammonium, sulfate, nitrate, black carbon (BC), and organic matter (OM)), and four blood lipid indicators (low-density lipoprotein cholesterol (LDLC), high-density lipoprotein cholesterol (HDLC), triglyceride (TG), and total cholesterol (TC)), we employed linear fixed-effects panel regression models. Results: Each interquartile range (IQR) increase in PM2.5 (lag 0-3 month) was associated with significant increases in LDLC (3.44%, 95% CI: 3.07-3.80) and TC (2.99%, 95% CI: 2.70-3.28), and a decrease in HDLC (-0.89%, 95% CI: -1.17 to -0.62). For constituents, ammonium and nitrate showed the strongest associations with LDLC (4.66% and 4.76%, respectively) and TC (3.72% and 3.60%, respectively). TG levels were positively associated with secondary inorganic aerosols, most notably sulfate (2.91%, 95% CI: 2.50-3.33). Significant negative correlations with HDLC were observed for BC (-0.46%, 95% CI: -0.72 to -0.19) and sulfate (-0.71%, 95% CI: -1.04 to -0.38). The exposure-response relationships between the constituents and blood lipid indicators were predominantly nonlinear, characterized by a plateau at higher concentration levels. Conclusion: Our results indicate that exposure to PM2.5 and its constituents, especially inorganic aerosol components, was strongly associated with adverse blood lipid levels. The findings of our study provide critical insights into policy development aimed at enhancing the management and control of PM2.5 pollution.
Background Long-term epidemiological trends of respiratory infectious diseases (RIDs) and their associations with meteorological factors and air pollutants remain understudied in recent 10 years in China. This study investigates temporal patterns of seven major RIDs during 2004–2018 and quantifies their relationships with meteorological variables and ambient pollutants, with the aim of informing evidence-based health policy and environmental interventions. Methods Data on seven RIDs were collected from the National Notifiable Infectious Disease Surveillance System, meteorological and air pollutants data were obtained from the meteorological monitoring stations and national air quality monitoring stations, respectively. Descriptive analyses were used to present trends, and joinpoint regression models were used to examine changes in incidence and mortality for each respiratory infectious disease and to estimate average annual percentage changes. A Distributed Lag Non-Linear Model (DLNM) with relative risk was applied to analyze the impact of meteorological conditions and air pollutants on RIDs. We also applied a time-series decomposition approach based on locally weighted regression to present the seasonality of seven RIDs. Results A total of 23,444,640 cases and 45,291 deaths caused by seven respiratory infectious diseases were recorded in China, and the national mean age-standardized incidence and mortality were 115.87/100,000 and 0.23/100,000, respectively; the change of incidence and mortality differed by age groups. sulfur dioxide (SO2) and particulate matter <10 μm (PM10) in air pollutants and relative humidity and sunshine hours in climatic factors had significant effects on most respiratory diseases in this study. Additionally, meteorological factors had a stronger impact on RIDs with an acute and short-term lag effect compared with air pollutants. Conclusions The prevention and control strategies for RIDs need to be formulated based on their own characteristics and shift from a single biomedical intervention model to an integrated approach encompassing medicine, environmental science, climate science, and socioeconomics.
Cognitive impairment is an increasingly public health concern. However, limited evidence exists regarding the combined effects of fine particulate matter (PM2.5) and extreme heat exposure on cognitive function. Here, data from 3042 adults aged >= 45 years without baseline cognitive impairment across four waves (2011-2018) of the China Health and Retirement Longitudinal Study were collected, and Cox proportional hazards models with time-dependent covariates (counting process format) were used to estimate hazard ratios (HRs) for combined exposure of heat and PM2.5. Over the follow-up period, 763 participants of 3042 were diagnosed with cognitive impairment. Per 10 mu g/m & sup3; increase in PM2.5 (HR = 1.342, 95% confidence intervals (CI): 1.288-1.399) and higher cumulative exposure to extreme heat (HR = 1.032, 95% CI: 1.001-1.063) were independently associated with increased risk of cognitive impairment. Furthermore, participants with joint exposure to high PM2.5 and high heat had a 76% greater risk of cognitive impairment (HR = 1.959, 95% CI: 1.343-2.857), compared to those with low PM2.5 and high heat (HR = 1.111, 95% CI: 0.795-1.553). Subgroup analyses further revealed heterogeneity in the associations, with stronger risks observed among participants aged <65 years, men, and residents in the central region. These findings highlight the urgent need for integrated environmental and public health strategies to mitigate the cognitive impacts of air pollution and climate-related heat stress.
Objectives The Big Data and Deep Learning in the surveillance of occupational cancers (BEST) project aimed to enhance occupational cancer surveillance in Italy by using large-scale registry linkages. It addressed two methodological challenges: controlling for multiple testing/selective inference when profiling occupational categories and cancers, and assessing robustness of inference in presence of unmeasured confounding. Methods Data were obtained through record linkage between the Italian cause-of-death registry (2005–2018) and the National Social Insurance Agency (INPS) database (1974–2018). Male blue-collar workers were classified by their longest held occupational sector, censoring the last 5 years before death. The study used a proportional cancer mortality design. Logistic regression models were fitted to estimate cause-specific mortality odds ratios (CMORs) for selected cancers and occupational sectors, adjusting for age, education, last region of residence, and year of death using the service sector as reference. Multiplicity was addressed through Q-Q plots with guide rails, q-values and control of false discovery rate, hierarchical Bayesian models and posterior rankings. E-values were calculated to assess the potential influence of unmeasured confounding. Results Elevated CMORs emerged for several cancers and industries, including lung cancer in construction and fishing, pleural cancer in shipyards, and sinonasal cancers in leather and woodworking trades. Findings remained consistent after multiple testing adjustments and sensitivity analyses using E-values. Conclusions We propose an integrated methodological framework that combines multiplicity-aware profiling and E-values to address selective inference from multiple testing and sensitivity to unmeasured confounding. The framework improves the interpretation and prioritization of signals in occupational cancer surveillance, providing robust insights to guide prevention strategies.
Per- and polyfluoroalkyl substances (PFAS) have dispersed widely into the environment from industrial and consumer uses, threatening water quality across the globe. There is limited information on PFAS occurrence in private wells. The objective of this study was to 1) detect and quantify concentrations of PFAS in residential tap water in rural Nebraska; 2) determine the PFAS profile across Nebraska drinking water, and 3) screen the risk of PFAS exposure to human health using a mixtures approach. Water samples were collected from randomly selected, rural residences around seven different known or suspected point sources in Nebraska. Samples were extracted and analyzed by liquid chromatography tandem mass spectrometry following U.S. Environmental Protection Agency (USEPA) Method 1633 for 40 PFAS analytes. Risk screening utilized the USEPA hazard index (HI) approach. Perfluorohexanesulfonic acid (PFHxS), perfluorobutanoic acid (PFBA), perfluorobutanesulfonic acid (PFBS), perfluorooctanoic acid (PFOA), perfluorooctanesulfonamide (PFOSA), and & sum;PFAS (sum of five PFAS) were included in the final analyses. At least one PFAS compound was detected in 98% of the samples. Median & sum;PFAS concentrations were 2.23 ng/L. There were significant differences between the median & sum;PFAS concentration and water source (X-2 = 13, p = 0.005), type of point source (X-2 = 7.94, p = 0.005), and town (X-2 = 58.0, p < 0.001). The range of & sum;PFAS concentration was greater for samples from private wells than other waters sources (max 108 ng/L). The HI ranged from 1.90-2120 for four PFAS but should be interpreted with extreme caution due to the limited nature and uncertainties with this screening tool. The PFAS risk profile from samples measured in this study represents diffuse (indirect) contamination due to lack of correlation between PFAS concentrations and distance from point source. Future studies in Nebraska should focus on non-point source random sampling complemented with non-targeted analytical approaches to provide a broader scope of PFAS potentially present.
Ambient air pollution is increasingly implicated in metabolic and inflammatory dysregulation, yet the evidence base specific to metabolic syndrome and white blood cell count remains fragmented, prompting a need to clarify whether exposure to major pollutants and particulate matter components materially contributes to these outcomes in adults. In this rapid review, conducted according to PRISMA-RR guidance, we synthesized twenty-six observational and clinical studies that examined associations between exposure to PM2.5, PM10, CO, NO2, O3, SO2 and five PM2.5 components including sulfate, nitrate, ammonium, black carbon and organic matter, and found that most investigations reported positive relationships with the prevalence of metabolic syndrome and elevated white blood cell count, with the most consistent signals observed for particulate matter across diverse geographic settings. Several studies suggested that exposure to particulate matter may activate systemic inflammatory processes, reflected in higher white blood cell count, which is biologically consistent with inflammation-related pathways linking pollution exposure to metabolic dysfunction. However, the strength and clarity of this pathway were limited by differences in exposure modelling, variation in metabolic syndrome criteria, and inconsistent adjustment for behavioral, clinical, and socioeconomic factors. Substantial evidence gaps persisted. Taken together, these findings point to a need for longitudinal, mechanistic and methodologically rigorous studies that apply refined exposure assessment, adopt standardized metabolic syndrome definitions, evaluate mediation and susceptibility profiles, and integrate atmospheric metrics with metabolic and inflammatory phenotyping in order to generate policy relevant evidence that generate policy-relevant evidence that supports multi-pollutant air quality management and the integration of environmental risk into clinical screening and prevention strategies for metabolic health in adults.
Objective: This study aims to explore the association of perceived greenspace exposure (PGE) with quality of life (QoL) and mental health among non-healthcare workers. Methods: A cross-sectional survey of non-healthcare workers was conducted in Hong Kong from March 2023 to December 2024. Information was collected by online questionnaires. We measured PGE using a 7-point Likert self-reported questionnaire about greenspace abundance (PGE 1), visibility (PGE 2), access (PGE 3) and usage (PGE 4) near participants' neighborhood/workplace. We assessed relationships between PGE with QoL and mental health using generalized linear and logistic regression models, and restricted cubic spline regression with four knots was used to examine the dose-response relationship. Results: Among 1380 non-healthcare workers, 547 (39.6 %) were male, the mean physical composite score (PCS) was 46.1 (standard deviation [SD]: 8.34) and the mean mental composite score (MCS) was 50.6 (14.59). We found 300 (21.7 %) participants with stress symptoms above DASS-21 cut-off, 512 (37.1 %) with anxiety symptoms above DASS-21 cut-off and 419 (30.4 %) with depression symptoms above DASS-21 cut-off. Positive relationships between PCS and four PGE domains (ss = 0.29, 95 % CI: 0.03-0.54 for PGE1; 0.41, 0.18, 0.64 for PGE2; 0.45, 0.21-0.70 for PGE3 and 0.33, 0.09-0.58 for PGE4), and between MCS and PGE3 (0.54, 0.11-0.96) were observed. Besides, higher PGE3 was associated with lower odds of anxiety (odds ratio [OR] = 0.93, 95 % confidential interval [CI]: 0.87-0.99) and depression (OR = 0.93, 95 % CI: 0.87-0.99). Subgroup analyses showed that PGE played different roles on workers among different genders and ages. Conclusion: PGE is associated with better quality of life and mental health. Urban planning should prioritize not only greenspace quantity but also, critically, its perceived accessibility near workplaces and neighborhoods.
Woodworkers are exposed to several potentially harmful agents, including microorganisms that grow in the wood. The most common fungal species in woodworking environments are Aspergillus, Penicillium, and Cladosporium spp. with occupational exposure to Aspergillus spp. posing a significant respiratory risk. This study aimed to assess exposure to Aspergillus spp. in two Portuguese woodworking environments and to perform a thorough analysis of Aspergillus fumigatus complex isolates collected from 13 DIY stores and 6 Carpentries in Lisbon Metropolitan Area. Sampling combined active and passive methods to assess microbial contamination. Aspergillus fumigatus isolates were analysed for their antifungal susceptibility, resistant mechanisms, mycotoxins production and cytotoxic potential in lung (A459) and liver (HepG2) cell lines. The MAS-100 presented Aspergillus sections Aspergilli and Flavi with the highest prevalence in DIY stores and Carpentries, respectively. A total of 1185 Aspergillus spp. were recovered, 270 identified as Aspergillus fumigatus sensu stricto growing at 37°C. None of those isolates was resistant to azoles, 99.07% of them produced gliotoxin and 39.9% of them produced cytotoxic effects in at least one cell line. This study comprehended a multi-approach that considered not only sampling methods but also the laboratory assays to be applied in the Aspergillus section Fumigati isolates recovered from two different woodworking environments, allowing a complete and robust analysis of this specific environment and species. Overall, the findings indicate that woodworkers are exposed to A. fumigatus isolates with relevant pathogenic traits, despite the absence of azole resistance, underscoring the need for continued environmental and occupational monitoring.
