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Record W4200163063 · doi:10.1038/s41598-021-03065-6

Environmental contaminants and the disproportionate prevalence of type-2 diabetes mellitus among Indigenous Cree women in James Bay Quebec, Canada

2021· article· en· W4200163063 on OpenAlexafffundabout
Aleksandra M. Zuk, Eric N. Liberda, Leonard J. S. Tsuji

Bibliographic record

VenueScientific Reports · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicToxic Organic Pollutants Impact
Canadian institutionsThe Scarborough HospitalToronto Metropolitan UniversityQueen's UniversityUniversity of Toronto
FundersCanadian Institutes of Health ResearchInstitute of Indigenous Peoples' HealthNiskamoon CorporationCree Board of Health and Social Services of James Bay
KeywordsType 2 Diabetes MellitusIndigenousDemographyConfidence intervalPoisson regressionMedicineEnvironmental healthBayDiabetes mellitusGeographyBiologyEcologyPopulationInternal medicineEndocrinology

Abstract

fetched live from OpenAlex

Indigenous populations are disproportionately affected by type 2 diabetes (T2DM) compared to non-Indigenous people. Of importance, the prevalence of T2DM is greater amongst females than males in First Nations communities, in contrast to higher male prevalence reported in non-Indigenous Canadians. Therefore, in this study we extend our previously published work with respect to females, and the potential association between environmental exposures to organochlorine pesticides, such as dichlorodiphenyltrichloroethane (DDT), and dichlorodiphenyldichloroethylene (DDE) to explain the greater prevalence of T2DM among Indigenous females compared to males. Using data from the Multi-Community Environment-and-Health Study, Principal Component Analysis (PCA), examined 9-polychlorinated biphenyl congeners, 7-organic pesticides, and 4-metal/metalloids. Modified Poisson regression with robust error variance estimated adjusted prevalence ratios (PR) and corresponding 95% confidence intervals (95% CI), regressing prevalent T2DM on the newly derived principal components (PC), adjusting for a priori covariates, including parity. We further examined the relationship between high detection concentrations of DDT and tertials of categorized DDE exposures on T2DM among Indigenous Cree women. Among 419 female participants, 23% (n = 95) had physician-diagnosed T2DM. PCA analysis show that DDT and Lead (Pb) loaded highly on the second axis (PC-2), although in opposite directions, indicating the different exposure sources. As previously published, T2DM was significantly associated with PC-2 across adjusted models, however, after further adjusting for parity in this analysis, T2DM was no longer significantly associated with increasing PC-2 scores (PR = 0.88, 95% 0.76, 1.03). Furthermore, we found that the highest detectable levels of DDT, and tertiles of DDE were significantly associated with prevalent T2DM in the fully adjusted model (PR = 1.93, 1.17, 3.19), and (PR = 3.58, 1.10, 11.70), respectively. This cross-sectional analysis suggests organochlorines, specifically, detectable high exposure concentrations of DDT and DDE are associated with prevalent type 2 diabetes, signifying a possible important link between parity and environmental organochlorines pesticides among Indigenous Cree women.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.099

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0030.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.003
GPT teacher head0.180
Teacher spread0.177 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2021
Admission routes3
Has abstractyes

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