Examining the influence of marital status on cognitive risk in a nationally representative sample of adults in India
Bibliographic record
Abstract
Abstract Background Influence of marital status on cognitive risk remains understudied in India with 17.7% of the global population. Methods To examine the influence of marital status (categorized as married, never married, widowed and other which included partnered, separated or divorced) on cognitive risk and to what extent marital status is a protective factor for cognitive decline. For this observational study design, we merged nationally representative harmonized Longitudinal Aging Study of India (LASI) and the harmonized Diagnostic Assessment of Dementia (LASI‐DAD) for 4096 adults 45 years and older and their spouses regardless of age from 2017 to 2019. We accounted for multistage, stratified, area probability cluster design of the complex survey using appropriate weights. The primary outcome was cognitive impairment based on cognition score without number series based on word recall, cognition tests and Jorm IQ code < 3.9 or > 3.9 or higher. The cognitive impairment was constructed as a 0/1 dummy variable coded 0 if the respondent was at low‐risk (mid‐tertile) or very low‐risk (top‐tertile) and coded 1 if the respondent was high‐risk (bottom‐tertile). We assessed proportion at risk for cognitive impairment by marital status and used chi‐square test to test significance at p<0.05 level. We ran logistic regression model on weighted population to examine the odds ratio of cognitive risk by marital status. Results Our weighted population was 4,716 adults, 64.0% were married, 0.93% were never married, 33.3% were widowed, and 1.8% were other. Those married had the lowest proportion of cognitive risk (43.0%) while never married had the highest proportion of cognitive risk (71.0%), followed by widowed (59.6%) and other (55.0%). In logistic regression, in comparison to married adults, cognitive risk was three times more likely for never married adults, AOR 3.17 [95% CI, 1.55‐6.48], and nearly two times more likely for widowed, AOR 1.58 [95% CI, 1.33‐1.88]. Conclusion Marital status likely functions as a social determinant of cognitive decline in the Indian context. These findings are relevant to U.S. and other countries as the harmonized LASI, is a sister study of the harmonized U.S. Health and Retirement Study and data can be leveraged using cross‐country comparisons.
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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 | 0.002 |
| 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 | 0.001 |
| 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".