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Record W7161943729 · doi:10.82308/20406

Correlates of iron status, hemoglobin and anemia in Inuit adults

2012· dissertation· en· W7161943729 on OpenAlexaboutno aff
Jennifer Jamieson

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsAnemiaIron deficiencySoluble transferrin receptorDietary ironHemoglobinIron-deficiency anemiaDietary diversityNutrientTransferrin receptor

Abstract

fetched live from OpenAlex

Iron deficiency and anemia have been paradoxically observed among circumpolar Inuit populations consuming diets rich in animal-source foods for decades, yet representative data are lacking to clarify the extent and association of both conditions. Little is known about the degree to which iron deficiency anemia can explain anemia for Inuit adults, who are at nutritional risk given the ongoing nutrition transition throughout the Arctic. The objectives of this thesis were: (i) to determine the iron status of Inuit adults (from depleted iron stores to iron overload), the prevalence of anemia, and the extent to which both iron deficiency and anemia occur together for men and women throughout adulthood; (ii) to assess dietary intakes of nutrients required for erythropoiesis and associations between traditional Inuit foods, iron status and anemia; and (iii) controlling for the effect of inflammation, to identify dietary and non-dietary correlates of iron status, hemoglobin, and risk of anemia. Data for this work were from the International Polar Year Inuit Health Survey, 2007-2008. This was a cross-sectional survey, with stratified random sampling of 2550 Inuit adults (60.9 % female) 18-89 years of age with an overall household response rate of 68 %. For objective (i) hemoglobin, serum ferritin, serum high-sensitivity C-reactive protein, and (on a subset n=1039) serum soluble transferrin receptor were measured. For objective (ii), a single 24 hour recall and a 42-item semi-quantitative food frequency questionnaire were utilized. Dietary iron inadequacy was calculated by adjusting the dietary iron intake distribution from the 24 hour recall by within-subject coefficients of variation for iron intake from previous dietary surveys with this population. For objective (iii) multivariate modeling was performed for serum ferritin, iron deficiency, elevated iron stores, hemoglobin, and anemia unexplained by iron deficiency (UA), controlling for potential confounders. Results showed that iron deficiency was pervasive among pre-menopausal women and explained a significant portion of the anemia in this lifestage despite adequate iron intake. For men, body iron stores were lower than expected based on dietary intake but not depleted. Rates of UA increased with age, being highest amongst men >50 years of age (30 %). Traditional food intake was an important correlate of iron status for both men and women, and was associated with reduced risk of iron deficiency among food insecure women. UA prevalence was highest in the most traditional Inuit region and was characterized by factors associated with a more traditional lifestyle including higher red blood cell eicosapentonoic acid (RBC EPA) proportions, elevated blood lead concentrations, low education levels, infections, and inflammation. The relationship between RBC EPA % and UA is a potentially important finding and should be further investigated for impact on RBC stability and hemolysis. Regional differences and correlates of UA across age-groups do not support the hypothesis that physiologically lower hemoglobin concentrations can explain the high rates of anemia observed among Inuit. Without clear evidence for revising the WHO cut-off for Inuit, anemia without evidence of iron deficiency should not be dismissed. Iron deficiency and anemia remain important public health concerns for Canadian Inuit adults.

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 score0.937
Threshold uncertainty score0.125

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.014
GPT teacher head0.338
Teacher spread0.325 · 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

Citations0
Published2012
Admission routes1
Has abstractyes

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