Modeling of Temporal Exposure to the Ambient Environment and Eczema Severity.
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ABSTRACT:
SUBMITTER: Thomas BR
PROVIDER: S-EPMC8713123 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Ambient noise characteristics are perused to assess the station performance of 27 newly constructed broadband seismic stations across Sikkim Himalaya and adjoining Himalayan foreland basin, installed to study the seismogenesis and subsurface structure of the region. Power spectral densities obtained at each station, compared against the global noise limits, reveal that observed vertical component noise levels are within the defined global limits. However, the horizontal components marginally overshoot the limits due to the tilt effect. Ambient noise conditions significantly vary with different installation techniques, analysis revealing that seismic sensors buried directly in the ground have reduced long-period noise in comparison to pier installations. Tectonic settings and anthropogenic activities are also noted to cause a significant rise across short-period and microseism noise spectrum, varying spatially and temporally across the region. Day-time records higher cultural noise than night-time, while the microseism noise dominates during the monsoonal season. An assessment of the effect of the nationwide lockdown imposed due to COVID-19 pandemic revealed a significant decrease in the short-period noise levels at stations installed across the foreland basin marked with higher anthropogenic activity. Our study summarizes the overall ambient noise patterns, validating the stability and performance of the seismic stations across the Sikkim Himalayas.
| S-EPMC8741811 | biostudies-literature
Project description:Air pollution epidemiology studies of ambient fine particulate matter (PM2.5) often use outdoor concentrations as exposure surrogates, which can induce exposure error. The goal of this study was to improve ambient PM2.5 exposure assessments for a repeated measurements study with 22 diabetic individuals in central North Carolina called the Diabetes and Environment Panel Study (DEPS) by applying the Exposure Model for Individuals (EMI), which predicts five tiers of individual-level exposure metrics for ambient PM2.5 using outdoor concentrations, questionnaires, weather, and time-location information. Using EMI, we linked a mechanistic air exchange rate (AER) model to a mass-balance PM2.5 infiltration model to predict residential AER (Tier 1), infiltration factors (Finf_home, Tier 2), indoor concentrations (Cin, Tier 3), personal exposure factors (Fpex, Tier 4), and personal exposures (E, Tier 5) for ambient PM2.5. We applied EMI to predict daily PM2.5 exposure metrics (Tiers 1-5) for 174 participant-days across the 13?months of DEPS. Individual model predictions were compared to a subset of daily measurements of Fpex and E (Tiers 4-5) from the DEPS participants. Model-predicted Fpex and E corresponded well to daily measurements with a median difference of 14% and 23%; respectively. Daily model predictions for all 174?days showed considerable temporal and house-to-house variability of AER, Finf_home, and Cin (Tiers 1-3), and person-to-person variability of Fpex and E (Tiers 4-5). Our study demonstrates the capability of predicting individual-level ambient PM2.5 exposure metrics for an epidemiological study, in support of improving risk estimation.
| S-EPMC6147059 | biostudies-literature
Project description:BackgroundThe Hand Eczema Severity Index (HECSI) is used to measure the severity of hand eczema. It is unclear what HECSI scores mean and what is the minimally important change (MIC). Furthermore, its responsiveness has not been studied.ObjectivesTo study the responsiveness and interpretability of the HECSI.MethodsThis was a prospective study covering two time points: baseline and after 4-12 weeks. Responsiveness was assessed using a criterion approach, with at least one-step improvement on the 'Photographic guide for severity of hand eczema' as the anchor for important improvement. Interpretability of single scores was determined by defining severity bands based on agreement with the anchor. For change scores, the smallest detectable change (SDC) was calculated in patients indicating no change and the MIC was obtained in patients indicating that they had changed using three methods: mean cutoff, receiver operating characteristic (ROC) curve and 95% limit.ResultsIn total, 294 patients participated (160 male, mean age 44·9 years). HECSI scores improved or deteriorated in parallel with the anchor. The area under the ROC curve was 0·86 (95% confidence interval 0·81-0·91). The final severity band for single scores had a κ-coefficient of agreement of 0·694: clear, 0; almost clear, 1-16; moderate, 17-37; severe, 38-116; very severe, ≥ 117. The SDC in 93 unchanged patients was 40·3 points. The obtained MIC values were all smaller than the SDC.ConclusionsThe HECSI has good responsiveness. This study gives meaning to HECSI scores, which can be applied to clinical decision making and the design of clinical trials. We recommend that an improvement of 41 points on the HECSI is regarded as the minimally measurable true change. What's already known about this topic? The Hand Eczema Severity Index (HECSI) is one of the most widely used measurement instruments to measure the severity of hand eczema. The HECSI has good reliability, but its responsiveness and interpretability have not been studied. What does this study add? This study shows good responsiveness of the HECSI. A severity grading for single scores is proposed. The smallest detectable change and minimally important change for improvement are determined. What are the clinical implications of this work? The obtained values help to interpret HECSI scores in daily practice and clinical studies, and may facilitate researchers in the calculation of sample sizes for clinical trials.
| S-EPMC7186841 | biostudies-literature
Project description:BackgroundLoss-of-function variants in the gene encoding filaggrin (FLG) are major determinants of eczema. We hypothesized that weakening of the physical barrier in FLG-deficient individuals may potentiate the effect of environmental exposures. Therefore, we investigated whether there is an interaction between FLG loss-of-function mutations with environmental exposures (pets and dust mites) in relation to the development of eczema.Methods and findingsWe used data obtained in early life in a high-risk birth cohort in Denmark and replicated the findings in an unselected birth cohort in the United Kingdom. Primary outcome was age of onset of eczema; environmental exposures included pet ownership and mite and pet allergen levels. In Copenhagen (n = 379), FLG mutation increased the risk of eczema during the first year of life (hazard ratio [HR] 2.26, 95% confidence interval [CI] 1.27-4.00, p = 0.005), with a further increase in risk related to cat exposure at birth amongst children with FLG mutation (HR 11.11, 95% CI 3.79-32.60, p < 0.0001); dog exposure was moderately protective (HR 0.49, 95% CI 0.24-1.01, p = 0.05), but not related to FLG genotype. In Manchester (n = 503) an independent and significant association of the development of eczema by age 12 mo with FLG genotype was confirmed (HR 1.95, 95% CI 1.13-3.36, p = 0.02). In addition, the risk increased because of the interaction of cat ownership at birth and FLG genotype (HR 3.82, 95% CI 1.35-10.81, p = 0.01), with no significant effect of the interaction with dog ownership (HR 0.59, 95% CI 0.16-2.20, p = 0.43). Mite-allergen had no effects in either cohort. The observed effects were independent of sensitisation.ConclusionsWe have demonstrated a significant interaction between FLG loss-of-function main mutations (501x and 2282del4) and cat ownership at birth on the development of early-life eczema in two independent birth cohorts. Our data suggest that cat but not dog ownership substantially increases the risk of eczema within the first year of life in children with FLG loss-of-function variants, but not amongst those without. FLG-deficient individuals may need to avoid cats but not dogs in early life.
| S-EPMC2504043 | biostudies-literature
Project description:BackgroundThe tremendous global health burden related to COVID-19 means that identifying determinants of COVID-19 severity is important for prevention and intervention. We aimed to explore long-term exposure to ambient air pollution as a potential contributor to COVID-19 severity, given its known impact on the respiratory system.MethodsWe used a cohort of all people with confirmed SARS-CoV-2 infection, aged 20 years and older and not residing in a long-term care facility in Ontario, Canada, during 2020. We evaluated the association between long-term exposure to fine particulate matter (PM2.5), nitrogen dioxide (NO2) and ground-level ozone (O3), and risk of COVID-19-related hospital admission, intensive care unit (ICU) admission and death. We ascertained individuals' long-term exposures to each air pollutant based on their residence from 2015 to 2019. We used logistic regression and adjusted for confounders and selection bias using various individual and contextual covariates obtained through data linkage.ResultsAmong the 151 105 people with confirmed SARS-CoV-2 infection in Ontario in 2020, we observed 8630 hospital admissions, 1912 ICU admissions and 2137 deaths related to COVID-19. For each interquartile range increase in exposure to PM2.5 (1.70 μg/m3), we estimated odds ratios of 1.06 (95% confidence interval [CI] 1.01-1.12), 1.09 (95% CI 0.98-1.21) and 1.00 (95% CI 0.90-1.11) for hospital admission, ICU admission and death, respectively. Estimates were smaller for NO2. We also estimated odds ratios of 1.15 (95% CI 1.06-1.23), 1.30 (95% CI 1.12-1.50) and 1.18 (95% CI 1.02-1.36) per interquartile range increase of 5.14 ppb in O3 for hospital admission, ICU admission and death, respectively.InterpretationChronic exposure to air pollution may contribute to severe outcomes after SARS-CoV-2 infection, particularly exposure to O3.
| S-EPMC9188786 | biostudies-literature
Project description:Contact structure, a critical driver of infectious disease transmission, is not completely understood and characterized for environmentally transmitted pathogens. In this study, we assessed the effects of temporal and spatial heterogeneity in animal contact structures on the dynamics of environmentally transmitted pathogens. We used real-time animal position data to describe contact between animals and specific environmental areas used for feeding and watering calves. The generated contact structure varied across days and among animals. We integrated animal and environmental heterogeneity into an agent-based simulation model for Escherichia coli O157 environmental transmission in cattle to simulate four different scenarios with different environmental bacteria concentrations at different areas. The simulation results suggest heterogeneity in environmental contact structure among cattle influences pathogen prevalence and exposure associated with each environment. Our findings suggest that interventions that target environmental areas, even relatively small areas, with high bacterial concentration can result in effective mitigation of environmentally transmitted pathogens.
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Project description:BackgroundAtopic dermatitis (AD) is a chronic inflammatory skin disease leading to substantial quality of life impairment with heterogeneous treatment responses. People with AD would benefit from personalised treatment strategies, whose design requires predicting how AD severity evolves for each individual.ObjectiveThis study aims to develop a computational framework for personalised prediction of AD severity dynamics.MethodsWe introduced EczemaPred, a computational framework to predict patient-dependent dynamic evolution of AD severity using Bayesian state-space models that describe latent dynamics of AD severity items and how they are measured. We used EczemaPred to predict the dynamic evolution of validated patient-oriented scoring atopic dermatitis (PO-SCORAD) by combining predictions from the models for the nine severity items of PO-SCORAD (six intensity signs, extent of eczema, and two subjective symptoms). We validated this approach using longitudinal data from two independent studies: a published clinical study in which PO-SCORAD was measured twice weekly for 347 AD patients over 17 weeks, and another one in which PO-SCORAD was recorded daily by 16 AD patients for 12 weeks.ResultsEczemaPred achieved good performance for personalised predictions of PO-SCORAD and its severity items daily to weekly. EczemaPred outperformed standard time-series forecasting models such as a mixed effect autoregressive model. The uncertainty in predicting PO-SCORAD was mainly attributed to that in predicting intensity signs (75% of the overall uncertainty).ConclusionsEczemaPred serves as a computational framework to make a personalised prediction of AD severity dynamics relevant to clinical practice. EczemaPred is available as an R package.
| S-EPMC8967258 | biostudies-literature
Project description:Exposure to high levels of air pollution during the pregnancy is associated with increased probability of preterm birth (PTB), a major cause of infant morbidity and mortality. New statistical methodology is required to specifically determine when a particular pollutant impacts the PTB outcome, to determine the role of different pollutants, and to characterize the spatial variability in these results. We develop a new Bayesian spatial model for PTB which identifies susceptible windows throughout the pregnancy jointly for multiple pollutants (PM(2.5) , ozone) while allowing these windows to vary continuously across space and time. We geo-code vital record birth data from Texas (2002-2004) and link them with standard pollution monitoring data and a newly introduced EPA product of calibrated air pollution model output. We apply the fully spatial model to a region of 13 counties in eastern Texas consisting of highly urban as well as rural areas. Our results indicate significant signal in the first two trimesters of pregnancy with different pollutants leading to different critical windows. Introducing the spatial aspect uncovers critical windows previously unidentified when space is ignored. A proper inference procedure is introduced to correctly analyze these windows.
| S-EPMC3422613 | biostudies-literature
Project description:BackgroundRetinoblastoma is a rare tumor of the retina, most commonly found in young children. Due to the rarity of this childhood cancer, few studies have been able to examine prenatal pesticide exposure as a risk factor.ObjectiveTo examine the relationship between childhood retinoblastoma and prenatal exposure to pesticides through residential proximity to agricultural pesticide applications.MethodsWe conducted a population-based case-control study using cases aged 5 and younger identified from the California Cancer Registry, and controls randomly selected from California birth certificates. Frequency matching cases to controls by age resulted in 221 cases of unilateral retinoblastoma and 114 cases of bilateral retinoblastoma, totaling 335 cases and 123,166 controls. Based on addresses from birth certificates we employed Pesticide Use Reports and land use information within a geographic information system approach to individually assess exposures to specific pesticides within 4000 m of the residence reported on birth certificates. The associations between retinoblastoma (all types combined and stratified by laterality) and individual pesticides were expressed as odds ratios estimates obtained from unconditional logistic regression models including a single pesticide, and from a hierarchical logistic regression model including all pesticides.ResultsWe found that exposures to acephate (OR: 1.70, 95% CI: 1.20, 2.41) and bromacil (OR: 1.87, 95% CI: 1.07, 3.26) were associated with increased risk for unilateral retinoblastoma. In addition to acephate, we found that pymetrozine (OR: 1.45, 95% CI: 1.00, 2.08) and kresoxim-methyl (OR: 1.60, 95% CI: 1.00, 2.56) were associated with retinoblastoma (all types combined).ConclusionOur findings suggest that certain types of prenatal ambient pesticide exposure from residing near agricultural fields may play a role in the development of childhood retinoblastoma.
| S-EPMC9901366 | biostudies-literature
Project description:Anecdotal reports of children experiencing eczema flares during winter and summer months along with global variation in eczema prevalence has fueled speculation that climate may modulate disease activity. The aim of this study was to determine whether long-term weather patterns affect the severity and persistence of eczema symptoms in children. We performed a prospective cohort study of US children (N=5,595) enrolled in PEER (Pediatric Eczema Elective Registry) between 2004 and 2012 to evaluate the effect of climate (daily temperature, daily sun exposure, daily humidity) on the severity of eczema symptoms. Odds ratios (ORs) were calculated for the patient-evaluated outcome of disease control. Multivariate logistic regression modeling adjusting for gender, race, income, and topical medication use demonstrated that higher temperature (OR=0.90, 95% confidence interval (CI): 0.87-0.93, P<0.001) and increased sun exposure (OR=0.93, 95% CI: 0.89-0.98, P=0.009) were associated with poorly controlled eczema. Higher humidity (OR=0.90, 95% CI: 0.812-0.997, P=0.04) was also associated with poorly controlled disease, but the statistical significance of this association was lost in our multivariate analysis (P=0.44).
| S-EPMC3869874 | biostudies-literature