825 resultados para Risk Assessment Code
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Moulds may produce a diversity of toxins such as aflatoxins, ochratoxins, trichothecenes, zearalenone, fumonisins and others. Although toxicological, environmental and epidemiological studies have addressed the problem of these toxins one by one, more than one mycotoxin are found usually in the same contaminated food. Risk assessment for humans potentially exposed to multimycotoxins suffers very much from the lack of adequate food consumption data. Furthermore, for a given mycotoxin, synergism and antagonism with other mycotoxins, found in the same food commodities, are not taken into account. Aflatoxin B1 and ochratoxin A belong to the most frequently occurring mycotoxins. This has repeatedly been demonstrated, however, normally, the risk resulting from their simultaneous occurrence is not considered. A descriptive study was developed to monitor air fungal contamination in one hospital food unit.
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The geography of Scotland, with a highly undulating hinterland, long and indented coastline, together with a large number of islands, means that much social and economic activity is largely located at the coast. The importance of the coast is further highlighted by the large number of ecosystem services derived from the coast. The threat posed by climate change, particularly current and future sea level rise, is of considerable concern and the associated coastal erosion and coastal flooding has the potential to have a substantial effect on the socioeconomic activity of the whole country. Currently, the knowledge base of coastal erosion is poor, which serves to hinder the current and future management of the coast. This research reported here aimed to establish four key aspects of coastal erosion within Scotland: the physical susceptibility of the coast to erosion; the assets exposed to coastal erosion; the vulnerability of communities to coastal erosion; and the coastal erosion risk to those communities. Coastal erosion susceptibility was modelled here within a GIS, using data for ground elevation, rockhead elevation, wave exposure and proximity to the open coast. Combining these data produced the Underlying Physical Susceptibility Model (UPSM), in the form of a 50 m2 raster of national coverage. The Coastal Erosion Susceptibility Model (CESM) was produced with the addition of sediment supply and coastal defence data, which then moderates the outputs of the UPSM. Asset data for dwellings, key assets, transport infrastructure, historic assets, and natural assets were used along with the UPSM and CESM to assess their degree of exposure to coastal erosion. A Coastal Erosion Vulnerability Model (CEVM) was produced using Experian Mosaic Scotland (a geodemographic classification which identifies 44 different social groups within Scotland) to classify populations based upon 11 vulnerability variables. Dwellings were assigned a CESM and CEVM score in order to establish their coastal erosion risk. This research demonstrated that the issue of coastal erosion will impact on a relatively low number of properties compared to those impacted by flooding (both coastal and fluvial) as many dwellings are already protected by coastal defences. There is therefore, a considerable future liability, and great pressure for coastal defences to be maintained and upgraded in their current form. The use of the CEVM is a novel inclusion within a coastal erosion assessment for Scotland. Use of the CEVM established that coastal erosion risk is not distributed equally amongst the Scottish coastal population and highlighted that risk can be reduced by either reducing exposure or reducing vulnerability. Thus far in Scotland, reducing exposure has been the primary management approach, which has a number of implications with regards social justice. This research identified the existing data gaps that should be addressed by future research in order to further improve coastal management in Scotland. Future research should focus on assessing historical coastal change rates on a national scale, improve modelling of national scale wave exposure, enhance the information held about current coastal defences and, determine the direct and indirect economic cost associated with the loss of different asset types. It is also necessary to clarify the social justice implications of using adaptation approaches to manage coastal erosion as well as establishing a method to communicate the susceptibility, exposure, vulnerability and risk aspects whilst minimising the potential negative impacts (e.g. property blight) of releasing such information.
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Although a clear correlation between levels of fungi in the air and health impacts has not been shown in epidemiological studies, fungi must be regarded as potential occupational health hazards. Fungi can have an impact on human health in four different ways: (1) they can infect humans, (2) they may act as allergens, (3) they can be toxigenic, or (4) they may cause inflammatory reactions. Fungi of concern in occupational hygiene are mostly non-pathogenic or facultative pathogenic (opportunistic) species, but are relevant as allergens and mycotoxins producers. It is known that the exclusive use of conventional methods for fungal quantification (fungal culture) may underestimate the results due to different reasons. The incubation temperature chosen will not be the most suitable for every fungal species, resulting in the inhibition of some species and the favouring of others. Differences in fungi growth rates may also result in data underestimation, since the fungal species with higher growth rates may inhibit others species’ growth. Finally, underestimated data can result from non-viable fungal particles that may have been collected or fungal species that do not grow in the culture media used, although these species may have clinical relevance in the context. Due to these constraints occupational exposure assessment, in setings with high fungal contamination levels, should follow these steps: Apply conventional methods to obtain fungal load information (air and surfaces) regarding the most critical scenario previously selected; Guideline comparation aplying or legal requirements or suggested limits by scientific and/or technical organizations. We should also compare our results with others from the same setting (if there is any); Select the most suitable indicators for each setting and apply conventional-culture methods and also molecular tools. These methodology will ensure a more real characterization of fungal burden in each setting and, consequently, permits to identify further measures regarding assessment of fungal metabolites, and also a more adequate workers health surveillance. The methodology applied to characterize fungal burden in several occupational environments, focused in Aspergillus spp. prevalence, will be present and discussed.
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Mycotoxins are an important group of naturally occurring substances known to contaminate a huge variety of agricultural products, feed and food commodities. The main concern is their widespread presence and toxic effects on humans and animals as they have been described as cytotoxic, nephrotoxic, hepatotoxic, teratogenic, immunosuppressive, mutagenic and/or carcinogenic. However, until now, risk assessments and regulations have usually been performed on individual mycotoxins despite humans and animals are being frequently exposed to a multitude of mycotoxins simultaneously. Moreover, even though some exposures through inhalation and dermal contact may potentially occur, only oral ingestion has been considered as the sole route of exposure in all the evaluations. However, more recent studies have also demonstrated airborne exposure to mycotoxins in different occupational settings with emphasis on agricultural professions. In these cases, skin contact with mold-infested substrates and inhalation of spore-borne toxins are the most important sources of exposure. Still, mycotoxins are not normally recongnize as na occupational hazard and exposure is different from the one ocurring by food intake. In this case, exposure is charaterized to be acute and simultaneous to other mycotoxins and also to fungi and dust. All these features increase the challenge implicated in the risk assessment process. Some topics will be presented and discussed in detailed such as: What occupational settings should be consider in this case; possible exposure routes; exposure characterization; how to assess exposure; co-exposure; aggregate exposure and cumulative risk assessment.
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Background: Nanotechnologies are developing very rapidly and nanomaterials (NMs) are increasingly being used in a wide range of applications in science, industry and biomedicine.
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There is a growing concern within public health about mycotoxin involvement in human diseases, namely those related to children. The MycoMix project (2012-2015), funded by the Portuguese Foundation for Science and Technology, gathered a multidisciplinary team aiming at answering several questions: 1) Are Portuguese children exposed daily to one or several mycotoxins through food? 2) Can this co-exposure affect children´s health? and 3) Are there interaction effect between mycotoxins? Mycomix results revealed that Portuguese children (< 3 years old, n=103) are exposed to multiple mycotoxins through food consumption. Cumulative risk assessment results revealed a potential health concern for the high percentiles of intake, specially for aflatoxins which are carcinogenic compounds. This fact assumes particular importance considering the interactive effects found in in vitro bioassays. These results highlight the need for a more accurate approach to assess the human exposure to mycotoxins6. Within the Mycomix project the assessment of mycotoxin exposure was based on calculations combining mycotoxin data in food with population data on food consumption. This approach does not consider some aspects as the inter-individual metabolism variation, the exposure through sources other than food and the heterogeneous distribution of mycotoxins in food. Exposure assessment of mycotoxins in Portuguese population through biomarkers is still missing and further studies are urgent to be developed. The European Human Biomonitoring Initiative (EHBMI), a proposal within the European Joint Programme, aims to advance the understanding of the extent of exposure to environmental chemicals across Europe and the impact on human health, by gathering national expertise in human biomonitoring domain. At national level Mycomix project uncovered the potential health risk of exposure of Portuguese children to multiple mycotoxins. The risk assessment expertise acquired within Mycomix, namely in analysis and toxicology of chemical mixtures, will be brought together as a contribute to EHBMI objectives.
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Historically, the health risk of mycotoxins had been evaluated on the basis of single-chemical and single-exposure pathway scenarios. However, the co-contamination of foodstuffs with these compounds is being reported at an increasing rate and a multiple-exposure scenario for humans and vulnerable population groups as children is urgently needed. Cereals are among the first solid foods eaten by child and thus constitute an important food group of their diet. Few data are available relatively to early stages child´s exposure to mycotoxins through consumption of cereal-based foods. The present study aims to perform the cumulative risk assessment of mycotoxins present in a set of cereal-based foods including breakfast cereals (BC), processed cereal-based foods (PCBF) and biscuits (BT), consumed by children (1 to 3 years old, n=75) from Lisbon region, Portugal. Children food consumption and occurrence of 12 mycotoxins (aflatoxins, ochratoxin A, fumonisins and trichothecenes) in cereal-based foods were combined to estimate the mycotoxin daily intake, using deterministic and probabilistic approaches. Different strategies were used to treat the left censored data. For aflatoxins, as carcinogenic compounds, the margin of exposure (MoE) was calculated as a ratio of BMDL (benchmark dose lower confidence limit) and aflatoxin daily exposure. For the remaining mycotoxins, the output of exposure was compared to the dose reference values (TDI) in order to calculate the hazard quotients (HQ, ratio between exposure and a reference dose). The concentration addition (CA) concept was used for the cumulative risk assessment of multiple mycotoxins. The combined margin of exposure (MoET) and the hazard index (HI) were calculated for aflatoxins and the remaining mycotoxins, respectively. Main results revealed a significant health concern related to aflatoxins and especially aflatoxin M1 exposure according to the MoET and MoE values (below 10000), respectively. HQ and HI values for the remaining mycotoxins were below 1, revealing a low concern from a public health point of view. These are the first results on cumulative risk assessment of multiple mycotoxins present in cereal-based foods consumed by children. Considering the present results, more research studies are needed to provide the governmental regulatory bodies with data to develop an approach that contemplate the human exposure and, particularly, children, to multiple mycotoxins in food. The last issue is particularly important considering the potential synergistic effects that could occur between mycotoxins and its potential impact on human and, mainly, children health.
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It is nowadays recognized that the risk of human co-exposure to multiple mycotoxins is real. In the last years, a number of studies have approached the issue of co-exposure and the best way to develop a more precise and realistic assessment. Likewise, the growing concern about the combined effects of mycotoxins and their potential impact on human health has been reflected by the increasing number of toxicological studies on the combined toxicity of these compounds. Nevertheless, risk assessment of these toxins, still follows the conventional paradigm of single exposure and single effects, incorporating only the possibility of additivity but not taking into account the complex dynamics associated to interactions between different mycotoxins or between mycotoxins and other food contaminants. Considering that risk assessment is intimately related to the establishment of regulatory guidelines, once the risk assessment is completed, an effort to reduce or manage the risk should be followed to protect public health. Risk assessment of combined human exposure to multiple mycotoxins thus poses several challenges to scientists, risk assessors and risk managers and opens new avenues for research. This presentation aims to give an overview of the different challenges posed by the likelihood of human co-exposure to mycotoxins and the possibility of interactive effects occurring after absorption, towards knowledge generation to support a more accurate human risk assessment and risk management. For this purpose, a physiologically-based framework that includes knowledge on the bioaccessibility, toxicokinetics and toxicodynamics of multiple toxins is proposed. Regarding exposure assessment, the need of harmonized food consumption data, availability of multianalyte methods for mycotoxin quantification, management of left-censored data and use of probabilistic models will be highlight, in order to develop a more precise and realistic exposure assessment. On the other hand, the application of predictive mathematical models to estimate mycotoxins’ combined effects from in vitro toxicity studies will be also discussed. Results from a recent Portuguese project aimed at exploring the toxic effects of mixtures of mycotoxins in infant foods and their potential health impact will be presented as a case study, illustrating the different aspects of risk assessment highlighted in this presentation. Further studies on hazard and exposure assessment of multiple mycotoxins, using harmonized approaches and methodologies, will be crucial towards an improvement in data quality and contributing to holistic risk assessment and risk management strategies for multiple mycotoxins in foodstuffs.
Resumo:
People, animals and the environment can be exposed to multiple chemicals at once from a variety of sources, but current risk assessment is usually carried out based on one chemical substance at a time. In human health risk assessment, ingestion of food is considered a major route of exposure to many contaminants, namely mycotoxins, a wide group of fungal secondary metabolites that are known to potentially cause toxicity and carcinogenic outcomes. Mycotoxins are commonly found in a variety of foods including those intended for consumption by infants and young children and have been found in processed cereal-based foods available in the Portuguese market. The use of mathematical models, including probabilistic approaches using Monte Carlo simulations, constitutes a prominent issue in human health risk assessment in general and in mycotoxins exposure assessment in particular. The present study aims to characterize, for the first time, the risk associated with the exposure of Portuguese children to single and multiple mycotoxins present in processed cereal-based foods (CBF). Portuguese children (0-3 years old) food consumption data (n=103) were collected using a 3 days food diary. Contamination data concerned the quantification of 12 mycotoxins (aflatoxins, ochratoxin A, fumonisins and trichothecenes) were evaluated in 20 CBF samples marketed in 2014 and 2015 in Lisbon; samples were analyzed by HPLC-FLD, LC-MS/MS and GC-MS. Daily exposure of children to mycotoxins was performed using deterministic and probabilistic approaches. Different strategies were used to treat the left censored data. For aflatoxins, as carcinogenic compounds, the margin of exposure (MoE) was calculated as a ratio of BMDL (benchmark dose lower confidence limit) to the aflatoxin exposure. The magnitude of the MoE gives an indication of the risk level. For the remaining mycotoxins, the output of exposure was compared to the dose reference values (TDI) in order to calculate the hazard quotients (ratio between exposure and a reference dose, HQ). For the cumulative risk assessment of multiple mycotoxins, the concentration addition (CA) concept was used. The combined margin of exposure (MoET) and the hazard index (HI) were calculated for aflatoxins and the remaining mycotoxins, respectively. 71% of CBF analyzed samples were contaminated with mycotoxins (with values below the legal limits) and approximately 56% of the studied children consumed CBF at least once in these 3 days. Preliminary results showed that children exposure to single mycotoxins present in CBF were below the TDI. Aflatoxins MoE and MoET revealed a reduced potential risk by exposure through consumption of CBF (with values around 10000 or more). HQ and HI values for the remaining mycotoxins were below 1. Children are a particularly vulnerable population group to food contaminants and the present results point out an urgent need to establish legal limits and control strategies regarding the presence of multiple mycotoxins in children foods in order to protect their health. The development of packaging materials with antifungal properties is a possible solution to control the growth of moulds and consequently to reduce mycotoxin production, contributing to guarantee the quality and safety of foods intended for children consumption.
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Humans can be exposed to multiple chemicals at once from a variety of sources, and human risk assessment of multiple chemicals poses several challenges to scientists, risk assessors and risk managers. Ingestion of food is considered a major route of exposure to many contaminants, namely mycotoxins, especially for vulnerable population groups, as children. A lack of sufficient data regarding mycotoxins children risk assessment, could contribute to an inaccuracy of the estimated risk. Efforts must be undertaken to develop initiatives that promote a broad overview of multiple mycotoxins risk assessment. The present work, developed within the MYCOMIX project, aims to assess the risk associated to the exposure of Portuguese children (< 3 years old) to multiple mycotoxins through consumption of foods primarily marketed for this age group. A holistic approach was developed applying deterministic and probabilistic tools to the calculation of mycotoxin daily intake values, integrating children food consumption (3-days food diary), mycotoxins occurrence (HPLC-UV, HPLC-FD, LC-MS/MS and GC-MS), bioaccessibility (standardized in vitro digestion model) and toxicological data (in vitro evaluation of cytotoxicity, genotoxicity and intestinal impact). A case study concerning Portuguese children exposure to patulin (PAT) and ochratoxin A (OTA), two mycotoxins co-occurring in processed cereal-based foods (PCBF) marketed in Portugal, was developed. Main results showed that there is low concern from a public health point of view relatively to PAT and OTA Portuguese children exposure through consumption of PCBF, considering the estimated daily intakes of these two mycotoxins (worst case scenarios, 22.930 ng/kg bw/day and 0.402 ng/kg bw/day, for PAT and OTA, respectively), their bioaccessibility and toxicology results. However, the present case study only concerns the risk associated with the consumption of PCBF and child diet include several other foods. The present work underlines the need to adopt a holistic approach for multiple mycotoxins risk assessment integrating data from exposure, bioacessibility and toxicity domains in order to contribute to a more accurate risk assessment.
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Nowadays, risks arising from the rapid development of oil and gas industries are significantly increasing. As a result, one of the main concerns of either industrial or environmental managers is the identification and assessment of such risks in order to develop and maintain appropriate proactive measures. Oil spill from stationary sources in offshore zones is one of the accidents resulting in several adverse impacts on marine ecosystems. Considering a site's current situation and relevant requirements and standards, risk assessment process is not only capable of recognizing the probable causes of accidents but also of estimating the probability of occurrence and the severity of consequences. In this way, results of risk assessment would help managers and decision makers create and employ proper control methods. Most of the represented models for risk assessment of oil spills are achieved on the basis of accurate data bases and analysis of historical data, but unfortunately such data bases are not accessible in most of the zones, especially in developing countries, or else they are newly established and not applicable yet. This issue reveals the necessity of using Expert Systems and Fuzzy Set Theory. By using such systems it will be possible to formulize the specialty and experience of several experts and specialists who have been working in petroliferous areas for several years. On the other hand, in developing countries often the damages to environment and environmental resources are not considered as risk assessment priorities and they are approximately under-estimated. For this reason, the proposed model in this research is specially addressing the environmental risk of oil spills from stationary sources in offshore zones.
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The sediments of Bear Creek near Baltimore, Maryland demonstrate substantial toxicity to benthic organisms, and contain a complex mixture of organic and inorganic contaminants. The present study maps the spatial extent and depth profile of toxicity and contamination in Bear Creek, and explores correlations between heavy metals, organic contaminants, and toxic responses. Two novel analytical techniques – handheld XRF and an antibody-based PAH biosensor – were applied to samples from the site to quantify total metals and total PAHs in sediments. By comprehensively assessing toxicity in Bear Creek, the present study provides data to inform future risk assessments and management decisions relating for the site, while demonstrating the benefits of applying joint biological assays and chemical assessment methods to sediments with complex contaminant mixtures.
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Background: Depression is a major health problem worldwide and the majority of patients presenting with depressive symptoms are managed in primary care. Current approaches for assessing depressive symptoms in primary care are not accurate in predicting future clinical outcomes, which may potentially lead to over or under treatment. The Allostatic Load (AL) theory suggests that by measuring multi-system biomarker levels as a proxy of measuring multi-system physiological dysregulation, it is possible to identify individuals at risk of having adverse health outcomes at a prodromal stage. Allostatic Index (AI) score, calculated by applying statistical formulations to different multi-system biomarkers, have been associated with depressive symptoms. Aims and Objectives: To test the hypothesis, that a combination of allostatic load (AL) biomarkers will form a predictive algorithm in defining clinically meaningful outcomes in a population of patients presenting with depressive symptoms. The key objectives were: 1. To explore the relationship between various allostatic load biomarkers and prevalence of depressive symptoms in patients, especially in patients diagnosed with three common cardiometabolic diseases (Coronary Heart Disease (CHD), Diabetes and Stroke). 2 To explore whether allostatic load biomarkers predict clinical outcomes in patients with depressive symptoms, especially in patients with three common cardiometabolic diseases (CHD, Diabetes and Stroke). 3 To develop a predictive tool to identify individuals with depressive symptoms at highest risk of adverse clinical outcomes. Methods: Datasets used: ‘DepChron’ was a dataset of 35,537 patients with existing cardiometabolic disease collected as a part of routine clinical practice. ‘Psobid’ was a research data source containing health related information from 666 participants recruited from the general population. The clinical outcomes for 3 both datasets were studied using electronic data linkage to hospital and mortality health records, undertaken by Information Services Division, Scotland. Cross-sectional associations between allostatic load biomarkers calculated at baseline, with clinical severity of depression assessed by a symptom score, were assessed using logistic and linear regression models in both datasets. Cox’s proportional hazards survival analysis models were used to assess the relationship of allostatic load biomarkers at baseline and the risk of adverse physical health outcomes at follow-up, in patients with depressive symptoms. The possibility of interaction between depressive symptoms and allostatic load biomarkers in risk prediction of adverse clinical outcomes was studied using the analysis of variance (ANOVA) test. Finally, the value of constructing a risk scoring scale using patient demographics and allostatic load biomarkers for predicting adverse outcomes in depressed patients was investigated using clinical risk prediction modelling and Area Under Curve (AUC) statistics. Key Results: Literature Review Findings. The literature review showed that twelve blood based peripheral biomarkers were statistically significant in predicting six different clinical outcomes in participants with depressive symptoms. Outcomes related to both mental health (depressive symptoms) and physical health were statistically associated with pre-treatment levels of peripheral biomarkers; however only two studies investigated outcomes related to physical health. Cross-sectional Analysis Findings: In DepChron, dysregulation of individual allostatic biomarkers (mainly cardiometabolic) were found to have a non-linear association with increased probability of co-morbid depressive symptoms (as assessed by Hospital Anxiety and Depression Score HADS-D≥8). A composite AI score constructed using five biomarkers did not lead to any improvement in the observed strength of the association. In Psobid, BMI was found to have a significant cross-sectional association with the probability of depressive symptoms (assessed by General Health Questionnaire GHQ-28≥5). BMI, triglycerides, highly sensitive C - reactive 4 protein (CRP) and High Density Lipoprotein-HDL cholesterol were found to have a significant cross-sectional relationship with the continuous measure of GHQ-28. A composite AI score constructed using 12 biomarkers did not show a significant association with depressive symptoms among Psobid participants. Longitudinal Analysis Findings: In DepChron, three clinical outcomes were studied over four years: all-cause death, all-cause hospital admissions and composite major adverse cardiovascular outcome-MACE (cardiovascular death or admission due to MI/stroke/HF). Presence of depressive symptoms and composite AI score calculated using mainly peripheral cardiometabolic biomarkers was found to have a significant association with all three clinical outcomes over the following four years in DepChron patients. There was no evidence of an interaction between AI score and presence of depressive symptoms in risk prediction of any of the three clinical outcomes. There was a statistically significant interaction noted between SBP and depressive symptoms in risk prediction of major adverse cardiovascular outcome, and also between HbA1c and depressive symptoms in risk prediction of all-cause mortality for patients with diabetes. In Psobid, depressive symptoms (assessed by GHQ-28≥5) did not have a statistically significant association with any of the four outcomes under study at seven years: all cause death, all cause hospital admission, MACE and incidence of new cancer. A composite AI score at baseline had a significant association with the risk of MACE at seven years, after adjusting for confounders. A continuous measure of IL-6 observed at baseline had a significant association with the risk of three clinical outcomes- all-cause mortality, all-cause hospital admissions and major adverse cardiovascular event. Raised total cholesterol at baseline was associated with lower risk of all-cause death at seven years while raised waist hip ratio- WHR at baseline was associated with higher risk of MACE at seven years among Psobid participants. There was no significant interaction between depressive symptoms and peripheral biomarkers (individual or combined) in risk prediction of any of the four clinical outcomes under consideration. Risk Scoring System Development: In the DepChron cohort, a scoring system was constructed based on eight baseline demographic and clinical variables to predict the risk of MACE over four years. The AUC value for the risk scoring system was modest at 56.7% (95% CI 55.6 to 57.5%). In Psobid, it was not possible to perform this analysis due to the low event rate observed for the clinical outcomes. Conclusion: Individual peripheral biomarkers were found to have a cross-sectional association with depressive symptoms both in patients with cardiometabolic disease and middle-aged participants recruited from the general population. AI score calculated with different statistical formulations was of no greater benefit in predicting concurrent depressive symptoms or clinical outcomes at follow-up, over and above its individual constituent biomarkers, in either patient cohort. SBP had a significant interaction with depressive symptoms in predicting cardiovascular events in patients with cardiometabolic disease; HbA1c had a significant interaction with depressive symptoms in predicting all-cause mortality in patients with diabetes. Peripheral biomarkers may have a role in predicting clinical outcomes in patients with depressive symptoms, especially for those with existing cardiometabolic disease, and this merits further investigation.
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International audience