Cognitive Functioning Trajectories and Their Association With Mental Health in Older Adults With Hypertension: Secondary Analysis of the Chinese Longitudinal Healthy Longevity Survey Data
Bibliographic record
Abstract
Background: There is a lack of research on the trajectories of cognitive functioning in older people with hypertension, as well as possible contributing factors and correlations between cognitive functioning and mental health. Objective: This study aimed to conduct a secondary longitudinal analysis to examine cognitive functioning trajectories and their associated factors in older people with hypertension. Methods: The data used in our study were retrieved from the Chinese Longitudinal Healthy Longevity Survey. The Chinese version of the Mini-Mental State Examination was used to assess cognitive functioning. The trajectories of cognitive functioning of older individuals with hypertension were determined by using group-based trajectory modeling. The binary logistic regression analyses were performed to examine how participant factors affected the trajectories of cognitive functioning in older individuals with hypertension. The relationships between cognitive functioning and mental health were investigated using multivariable linear regression models. Data were analyzed using SPSS (version 20.0; SPSS Inc) and Stata (version 16.0; StataCorp LLC). Results: A total of 642 older people with hypertension were included. Cognitive functioning was categorized into 2 trajectories according to group-based trajectory modeling: "rapid decline" (48/642, 7.9%) and "slow decline" (594/642, 92.1%). Binary logistic regression results showed that older adults with hypertension aged equal to or greater than 80 years had an elevated risk of rapid decline in cognitive functioning (odds ratio 5.484, 95% CI 2.365-12.719), and higher score in mental health was the protector of rapid decline in cognitive functioning during the following 13 years (odds ratio 0.918, 95% CI 0.852-0.988). In the unadjusted model, mental health was positively associated with cognitive functioning (β=.246, 95% CI 0.125-0.234, P<.001), and this association was maintained after partial or complete adjustment for covariates (β=.159, 95% CI 0.059-0.174, P<.001; β=.138, 95% CI 0.043-0.158, P=.001). Subgroup analyses by age showed that this positive correlation was only seen in the 60-69 years age group (β=.183, 95% CI 0.036-0.193, P=.004), while subgroup analyses by sex revealed that the association between these 2 indicators was no longer presented among males in the fully adjusted model (β=.082, 95% CI -0.024 to 0.119, P=.19), and BMI fully stratification demonstrated this association persisted in the healthy weight group (β=.125, 95% CI 0.039-0.210, P=.004). Conclusions: Our research showed that the decline in cognitive functioning is associated with lower mental health and occurs more rapidly in older adults with hypertension who are older than 80 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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
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".