The Association between Female Reproductive Factors and Subjective and Objective Cognitive Function: a Cross-sectional Analysis from the Pingyin Cohort
Bibliographic record
Abstract
Background The association between female reproductive factors and cognitive function was unclear, there still lack studies on female reproductive factors and subjective cognitive function. Objective Exploring the relationship between female reproductive factors and subjective or objective cognitive function, and providing theoretical basis for the prevention and intervention of cognitive decline and dementia. Methods The baseline survey was conducted in July 2023 in Pingyin, Jinan (in three townships). After using a multi-stage cluster random sampling method, 2 165 valid participants aged 45-70 were recruited at baseline. We collected sociodemographic data, medical histories, lifestyle factors, and female reproductive factors through a self-designed comprehensive questionnaire. The subjective and objective cognitive function of participants were evaluated by the Subjective Cognitive Decline-Questionnaire 9 (SCD-Q9) and Montreal Cognitive Assessment Scale-Basic (MoCA-B), respectively. In addition, we also collected anthropometric data (included height and weight) and blood samples (to get APOE e4 alleles). Multivariate Logistic regression and Local weighted regression (Loess) were used to analyze the influence of female reproductive factors on cognitive function and to detect potential nonlinear relationships between age at menarche, age at menopause, length of reproductive period and MoCA-B scores. Results This study was based on a baseline population and included 1 044 postmenopausal women. The prevalence of abnormal SCD-Q9 scores was 48.37% (505/1 044), while the prevalence of abnormal MoCA-B scores was 67.43% (704/1 044). Women who had 3 or more children had a lower risk of subjective cognitive decline compared with those who had 1 or fewer children (OR=0.59, 95%CI=0.36-0.98). Women with a breastfeeding duration <6 months had a higher risk of subjective cognitive decline compared with those with a breastfeeding duration of 6-12 months (OR=3.69, 95%CI=1.03-13.16). Age at menarche >18 years (OR=1.91, 95%CI=1.09-3.35), age at menopause ≤45 years (OR=1.61, 95%CI=1.00-2.62), and reproductive period ≤30 years (OR=1.56, 95%CI=1.07-2.29) or >40 years (OR=2.22, 95%CI=1.05-4.72) were all associated with poorer objective cognitive function (P<0.05). Loess analysis revealed an inverted "J-shaped" relationship between age at menarche, age at menopause, reproductive period and MoCA-B scores. Conclusion Women with more children (≥3) have a lower risk of subjective cognitive decline and women with shorter breastfeeding duration (<6 months) have a higher risk of subjective cognitive decline. Age at menarche >18 years, early menopause (≤45 years), and excessively long or short reproductive periods are all associated with poorer objective cognitive function. We should pay attention to the influence of female reproductive factors on cognitive function in order to delay the process of cognitive decline.
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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 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".