Association of Age and Anemia With Adiponectin Serum Levels in Normal-Weight Japanese Women
Bibliographic record
Abstract
Background: Adiponectin serum levels are affected by sex, ethnicities, adiposity, age and several pathological conditions such as anemia. The prevalence of hyperadiponectinemia (? 20 mg/L) in relation to anemia (hemoglobin < 12 g/dL) was examined in normal-weight Japanese women. Methods: Serum adiponectin and blood hemoglobin were measured in 311 young women aged 18 - 24 years (A), 148 of their middle-aged mothers aged 39 - 60 years (B) and 322 community-dwelling women aged ? 65 years (C) with a mean body mass index (BMI) of 20.4, 22.0 and 22.4 kg/m 2 , respectively. Elderly women were subdivided into three age groups: between 65 and 74 years (n = 95, X), between 75 and 84 years (n = 176, Y) and older than 85 years (n = 51, Z). Results: The prevalence of hyperadiponectinemia (A: 3.9%, B: 3.4%, C: 22.7%, P < 0.001) was low and serum adiponectin (A: 11.5 ± 4.3 mg/L, B: 11.8 ± 4.9 mg/L, C: 15.3 ± 7.8 mg/L, P < 0.001) did not change until middle-aged but increased thereafter in a stepwise fashion (X: 18.9%, Y: 22.7%, Z: 35.3%, P = 0.07 and X: 13.9 ± 6.9 mg/L, Y: 15.1 ± 7.7 mg/L, Z: 18.7 ± 8.6 mg/L, P = 0.001, respectively). There were inverse associations of adiponectin with age (r = -0.201, P < 0.001) and hemoglobin (r = -0.318, P < 0.001) in elderly women but not even in young and middle-aged women combined. Furthermore, anemia was associated with higher prevalence of hyperadiponectinemia (34.8% vs. 20.6%, P = 0.01) and higher serum adiponectin (18.3 ± 9.4 mg/L vs. 14.5 ± 7.1 mg/L, P < 0.001) in elderly women but not in younger and middle-aged women. Conclusions: In normal-weight Japanese women, the prevalence of hyperadiponectinemia and serum adiponectin were increased and associated with anemia at 65 years of age and older. J Clin Med Res. 2019;11(5):367-374 doi: https://doi.org/10.14740/jocmr3821
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".