Losing Social Connections as We Age and Links to Hypertension Risk in Adults in Canada: A Gender-Sensitive Secondary Data Analysis Study of the Canadian Longitudinal Study on Aging (2011-2021)
Bibliographic record
Abstract
BACKGROUND: Hypertensive disorders of pregnancy (HDP) are linked to long-term cardiovascular changes, but their impact on brain structure, particularly white matter hyperintensities (WMH), remains unclear.Gender-related factors like low education and income levels are associated with higher HDP incidence, but their role in the HDP-WMH relationship is unknown.In this study we examined whether sex-related factors modify the HDP-WMH association.METHODS: We included 1350 UK Biobank women (270 with HDP, 1080 without), aged 50 AE 7 years at recruitment (2006-2010) with at least 1 live birth.HDP was identified via ICD codes and self-reports, and WMH volume (measured using MRI, 2014-2022) was standardized for head size.Women with HDP were matched 1:4 to women with normotensive pregnancies according to delivery year and parity.Linear regression was used to assess HDP-WMH associations, incorporating a social index (sum of dichotomized sex-related variables) and its interaction with HDP, adjusting for age, age at first delivery, parity, waist-tohip ratio, gestational diabetes, depression, smoking, sleep, and alcohol use.RESULTS: WMH volumes were similar across groups (HDP: 3.0 mL [95% CI, 2.7-3.5];non-HDP: 2.7 mL [95% CI, 2.5-2.9]), and social index scores (HDP: 5.8 [95% CI, 5.5-6.1];non-HDP: 5.4 [95% CI, 5.3-5.6]).Multivariate analysis showed an association between HDP and WMH (b 0.4; 95% CI, 0.1-0.8)and between social index and WMH (b 0.11; 95% CI, 0.04-0.19).No interactions between social index and HDP (P 0.145) were found.CONCLUSIONS: HDP and sex-related factors are independently associated with increased WMH, with no interaction between them, highlighting the need to address social determinants and monitor brain health in women with HDP.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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 | 0.000 |
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 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".