Hypertension and High Blood Pressure Are Associated With Dementia Among Chinese Dwelling Elderly: The Shanghai Aging Study
Bibliographic record
Abstract
Background: To explore the association between blood pressure and cognition in older participants in the Shanghai Aging Study. Methods: Data were drawn from 3,327 participants at the baseline of Shanghai Aging Study. History of hypertension was asked and confirmed from participants’ medical records. Systolic blood pressure (SBP) and diastolic blood pressure (DBP) were measured by research nurses in the early morning. Participants were diagnosed with ‘cognitive normal’, ‘mild cognitive impairment (MCI)’, or ‘dementia’ by neurologists using DSM-IV and Petersen criteria. Multivariate logistic regression was used to evaluate the association between the history of hypertension, duration of hypertension, SBP, DBP, or classification of blood pressure and cognitive function. Generalized linear model was used to assess the relation between duration of hypertension, SBP, or DBP and Mini Mental State Examination (MMSE). Results: A significantly higher proportion of hypertension [78 (76.5%)] was found in participants with dementia than in those with MCI [347 (59.3%)] and cognitive normal [1,350 (51.1%)] (P < 0.0001). Participants with dementia had significantly higher SBP [157.6 (26.1) mmHg] than those with MCI [149.0 (23.7) mmHg] and cognitive normal [143.7 (22.6) mmHg] (P < 0.0001). After adjusted for sex, age, education, living alone, Body Mass Index, anxiety, depression, heart disease, diabetes, and stroke, the likelihood of having dementia was positively associated with history of hypertension (OR=2.10, 95%CI: 1.22, 3.61), duration of hypertension (OR=1.02 per increment year, 95%CI: 1.01,1.04), higher SBP (OR=1.14 per increment of 10mmHg, 95%CI: 1.04, 1.25), higher DBP (OR=1.22 per increment of 10mmHg, 95%CI: 1.02, 1.45), moderate hypertension (OR=2.09, 95%CI: 1.10, 3.99), or severe hypertension (OR=2.45, 95%CI: (1.20, 4.99)]. MMSE score was inversely correlated to duration of hypertension (β=-0.0088 per increment year, 95%CI: -0.0158, -0.0018, P=0.0132), SBP (β=-0.0655 per increment of 10mmHg, 95%CI: -0.1022, -0.0288, P=0.0005), and DBP (β=-0.1230 per increment of 10mmHg, 95%CI: -0.1915, -0.0545, P=0.0004). Conclusion: Our results suggest that hypertension and high blood pressure may be potential risk factors for dementia. Blood pressure management for the elderly may be important for maintaining cognitive vitality.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".