Background: Molar sums are often used to quantify total phthalate exposure, but they do not capture patterns of exposure to multiple phthalates.
Objective: To introduce an exposure burden score method for quantifying exposure to phthalate metabolites and examine the association between phthalate burden scores and Homeostatic Model Assessment for Insulin Resistance (HOMA-IR).
Methods: We applied item response theory (IRT) to data from 3474 adults aged 20-60 years in the 2013-2018 National Health and Examination Survey (NHANES) to quantify latent phthalate exposure burden from 12 phthalate metabolites. We compared model fits of three IRT models that used different a priori groupings (general phthalate burden; low molecular weight (LMW) and high molecular weight (HMW) burdens; and LMW, HMW and DEHP burden), and used the best fitting model to estimate phthalate exposure burden scores. Regression models assessed the covariate-adjusted association between phthalate burden scores and HOMA-IR. We compared findings to those using molar sums. In secondary analyses, we examined how the IRT model could be used for data harmonization when a subset of participants are missing some phthalate metabolites, and accounted for measurement error of the phthalate burden scores in estimating associations with HOMA-IR through a resampling approach using plausible value imputation.
Results: A three correlated factors model (LMW, HMW and DEHP burdens) provided the best fit. One interquartile range (IQR) increase in DEHP burden score was associated with 0.094 (95% CI: 0.022, 0.164, p = 0.010) increase in log HOMA-IR, co-adjusted for LMW and HMW burden scores. Findings were consistent when using log molar sums. Associations of phthalate burden and insulin resistance were also consistent when participants were simulated to be missing some phthalate metabolites, and when we accounted for measurement error in estimating burden scores.
Conclusion: Both phthalate molar sums and burden scores are sensitive to associations with insulin resistance. Phthalate burden scores may be useful for data harmonization.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10580272 | PMC |
http://dx.doi.org/10.1038/s41370-023-00535-z | DOI Listing |
BMC Health Serv Res
January 2025
Indiana University School of Medicine, 410 W 10th St, Suite 2000A, Indianapolis, IN, 46202, USA.
Background: Individuals with Sickle Cell Disease (SCD) are a minoritized and marginalized community that have disparate health outcomes as a result of systemic racism and disease-related stigma. The purpose of this study was to determine the psychosocial risk factors for families caring for children with SCD at a pediatric SCD center through use of the Psychosocial Assessment Tool (PAT), a validated caregiver-report screener.
Methods: The PAT was administered annually during routine clinical visits and scored by the SCD Social Worker to provide tailored resources to families.
BMC Public Health
January 2025
Department of Public Health and Primary Care, Leiden University Medical Centre, Hippocratespad 21, Leiden, Netherlands.
Background: eHealth literacy (eHL) is positively associated with health-related behaviors and outcomes. Previous eHL studies primarily collected data from online users and seldom focused on the general population in low- and middle-income countries (LMIC). Additionally, knowledge about factors that affect eHL is limited.
View Article and Find Full Text PDFMed Care
January 2025
John Ware Research Group (JWRG), Watertown, MA.
Background: Comprehensive health-related quality of life (QOL) assessment under severe respondent burden constraints requires improved single-item scales for frequently surveyed domains. This article documents how new single-item-per-domain (SIPD) QOL General (QGEN-8) measures were constructed for domains common to SF-36 and results from the first psychometric tests comparing scores for the new measure in relation to those for the SF-36 profile and summary components.
Research Design: Online NORC surveys of adults, ages 19-93 (mean=52 y) representing the US population in 2020 (N=1648) included QGEN-8 and SF-36 items measuring physical (PF), social (SF), role physical (RP) and role emotional (RE) functioning and feelings of bodily pain (BP), vitality (VT), and mental health (MH).
Background: Despite the significant public health burden of maternal mental health disorders in sub-Saharan Africa (SSA), limited data are available on their effects on early childhood development (ECD), nutritional status, and child health in the region.
Aims: This study investigated the association between maternal mental health and ECD, nutritional status, and common childhood illnesses, while controlling for biological, social, financial, and health-related factors and/or confounders.
Method: As part of the Innovative Partnership for Universal and Sustainable Healthcare (i-PUSH) program evaluation study, initiated in November 2019, a cohort of low-income rural families, including pregnant women or women of childbearing age with children under five, was recruited for this study.
NEJM AI
October 2024
Google, Mountain View, CA, USA.
Background: Using artificial intelligence (AI) to interpret chest X-rays (CXRs) could support accessible triage tests for active pulmonary tuberculosis (TB) in resource-constrained settings.
Methods: The performance of two cloud-based CXR AI systems - one to detect TB and the other to detect CXR abnormalities - in a population with a high TB and human immunodeficiency virus (HIV) burden was evaluated. We recruited 1978 adults who had TB symptoms, were close contacts of known TB patients, or were newly diagnosed with HIV at three clinical sites.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!