Cardiometabolic health across menopausal years is linked to white matter hyperintensities up to a decade later
Bibliographic record
Abstract
Introduction The menopause transition is associated with several cardiometabolic risk factors. Poor cardiometabolic health is further linked to microvascular brain lesions, which can be detected as white matter hyperintensities (WMHs) using T2-FLAIR magnetic resonance imaging (MRI) scans. Females show higher risk for WMHs post-menopause, but it remains unclear whether changes in cardiometabolic risk factors underlie menopause-related increase in brain pathology. Methods In this study, we assessed whether cross-sectional measures of cardiometabolic health, including body mass index (BMI) and waist-to-hip ratio (WHR), blood lipids, blood pressure, and long-term blood glucose (HbA1c), as well as longitudinal changes in BMI and WHR, differed according to menopausal status at baseline in 9,882 UK Biobank females (age range 40–70 years, n premenopausal = 3,529, n postmenopausal = 6,353). Furthermore, we examined whether these cardiometabolic factors were associated with WMH outcomes at the follow-up assessment, on average 8.78 years after baseline. Results Postmenopausal females showed higher levels of baseline blood lipids (HDL <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="IM5"><mml:mi>β</mml:mi></mml:math> = 0.14, p &lt; 0.001, LDL <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="IM7"><mml:mi>β</mml:mi></mml:math> = 0.20, p &lt; 0.001, triglycerides <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="IM9"><mml:mi>β</mml:mi></mml:math> = 0.12, p &lt; 0.001) and HbA1c ( <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="IM11"><mml:mi>β</mml:mi></mml:math> = 0.24, p &lt; 0.001) compared to premenopausal women, beyond the effects of age. Over time, BMI increased more in the premenopausal compared to the postmenopausal group ( <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="IM13"><mml:mi>β</mml:mi></mml:math> = −0.08, p &lt; 0.001), while WHR increased to a similar extent in both groups ( <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="IM15"><mml:mi>β</mml:mi></mml:math> = −0.03, p = 0.102). The change in WHR was however driven by increased waist circumference only in the premenopausal group. While the group level changes in BMI and WHR were in general small, these findings point to distinct anthropometric changes in pre- and postmenopausal females over time. Higher baseline measures of BMI, WHR, triglycerides, blood pressure, and HbA1c, as well as longitudinal increases in BMI and WHR, were associated with larger WMH volumes ( <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="IM17"><mml:mi>β</mml:mi></mml:math> range = 0.03–0.13, p ≤ 0.002). HDL showed a significant inverse relationship with WMH volume ( <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="IM20"><mml:mi>β</mml:mi></mml:math> = −0.27, p &lt; 0.001). Discussion Our findings emphasise the importance of monitoring cardiometabolic risk factors in females from midlife through the menopause transition and into the postmenopausal phase, to ensure improved cerebrovascular outcomes in later years.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.000 | 0.001 |
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 teacher head, 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".