ArticleEnvironmental epidemiology (Philadelphia, Pa.)2021
Multipollutant, longitudinal analysis of the association between urinary tungsten and incident diabetes in a rural population.
Article in Environmental epidemiology (Philadelphia, Pa.), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed, 13 citations in OpenAlex.
- Associations between metals and metabolomic profiles related to diabetes among adults in a rural region.Environmental research · 2024Article
- Tungsten toxicity and carcinogenesis.Advances in pharmacology (San Diego, Calif.) · 2023Article
- Development and application of an evidence-based directed acyclic graph to evaluate the associations between metal mixtures and cardiometabolic outcomes.Epidemiologic methods · 2023Article
- Potential Roles of Metals in the Pathogenesis of Pulmonary and Systemic Hypertension.International journal of biological sciences · 2023Review
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 4 institutions in 1 country.
Funding
Abstract
backgroundCross-sectional studies suggest tungsten (W) exposure may be associated with diabetes. We assessed longitudinal associations between urinary W and fasting glucose, 2-hour glucose, insulin resistance (HOMA-IR), β-cell function (HOMA-β), and incident type 2 diabetes.
methodsWe used data from 1,609 Hispanic and non-Hispanic White adults with 20 to 74 years of age residing in rural Colorado and participating in the San Luis Valley Diabetes Study. Urinary metal exposure values were measured at baseline and natural log-transformed. We assessed longitudinal associations between urinary W and continuous outcome measures using linear-mixed effect models and associations with incident diabetes using Fine and Gray competing risks regression models (competing event = all-cause mortality). The main adjustment set of covariates included: age, sex, ethnicity, education, smoking status, hypertension, body mass index, caloric intake, alcohol intake, and urinary creatinine levels. Secondary models were further adjusted for arsenic, cadmium, and lead exposures. We assessed whether sex or ethnicity were effect modifiers.
resultsAt baseline, the median W concentration was 0.22 μg/L (interquartile range = 0.20, 0.59). In the main cross-sectional analyses, lnW levels were significantly associated with 3% higher lnHOMA-IR (95% CI = 1 to 5). In the main longitudinal models, lnW was significantly associated with 1% higher natural log-transformed fasting glucose (95% CI = <1 to 1), 3% higher natural log-transformed HOMA-IR (95% CI = 2 to 5), and 28% higher incident diabetes (subdistribution hazard ratio=1.28, 95% CI = 1.09 to 1.50). Results remained significant when further adjusting for other metals. We observed evidence for effect modification by sex and ethnicity.
conclusionUrinary W was longitudinally associated with adverse metabolic health indicators.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.