Characterization of environmental exposures to population subgroups within the National Children's Study (NCS), or other large-scale human environmental health studies is essential for developing a high-quality data platform for subsequent investigations. A computational formulation utilizing the tiered exposure ranking framework is presented for calculating inhalation exposure indices (EIs) for population subgroups. This formulation employs a probabilistic approach and combines information from diverse, publicly available exposure-relevant databases and information on biological mechanisms, for ranking study locations or population subgroups with respect to potential for specific end point-related environmental exposures. These EIs capture and summarize, within a set of numerical values/ranges, complex distributions of potential exposures to multiple airborne contaminants. These estimates capture spatial and demographic variability within each study segment, and allow for the relative comparison of study locations based on different statistical metrics of exposures. The EI formulation was applied to characterize and rank segments within Queens County, NY, which is one of the Vanguard centers for the NCS. Inhalation EI estimates relevant to respiratory outcomes, and potentially to pregnancy outcomes (low birth weight and preterm birth rates) were calculated at the study segment level. Results indicate that there is substantial variability across the study segments in Queens County, NY, and within segments, and showed an exposure gradient across the study segments that can help guide and target environmental and personal exposure sampling efforts in this county. The results also serve as an example application of the EI for use in other exposure and outcome studies.
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http://dx.doi.org/10.1038/jes.2012.99 | DOI Listing |
Acta Neuropathol
January 2025
Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.
Alzheimers Res Ther
December 2024
Faculty of Health, Medicine and Life Sciences, Mental Health and Neuroscience Research Institute, Alzheimer Centre Limburg, Maastricht University, Maastricht, The Netherlands.
Background: Although separate lines of research indicated a moderating role of sex in both sleep-wake disruption and in the interindividual vulnerability to Alzheimer's disease (AD)-related processes, the quantification of sex differences in the interplay between sleep-wake dysregulation and AD pathology remains critically overlooked. Here, we examined sex-specific associations between circadian rest-activity patterns and AD-related pathophysiological processes across the adult lifespan.
Methods: Ninety-two cognitively unimpaired adults (mean age = 59.
Clin Endocrinol (Oxf)
December 2024
Department of Pediatrics, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
Background: Osteocalcin is a metabolic active hormone, which correlates positively with bone formation and inversely with body mass index and waist circumference in adults.
Objectives: To investigate whether osteocalcin in infancy and early childhood were related to childhood growth or body composition.
Methods: A Swedish longitudinal birth cohort with blood samples from 551 children from birth until 5 years of age.
Intensive Care Med
December 2024
Department of Perioperative Medicine, Barts Health NHS Trust, London, UK.
Alzheimers Dement
December 2024
Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Huddinge, Sweden.
Introduction: This study investigated the associations of brain age gap (BAG)-a biological marker of brain resilience-with life exposures, neuroimaging measures, biological processes, and cognitive function.
Methods: We derived BAG by subtracting predicted brain age from chronological age in 739 septuagenarians without dementia or neurological disorders. Robust linear regression models assessed BAG associations with life exposures, plasma inflammatory and metabolic biomarkers, magnetic resonance imaging, and cerebrospinal fluid biomarkers of neurodegeneration and vascular brain injury, and cognitive performance.
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