Couple concordance in diabetes, hypertension and dyslipidaemia in urban India and Pakistan and associated socioeconomic and household characteristics and modifiable risk factors
Bibliographic record
Abstract
Background: Concordance in chronic disease status has been observed within couples. In urban India and Pakistan, little is known about couple concordance in diabetes, hypertension, and dyslipidaemia and associated socioeconomic characteristics and modifiable risk factors.Methods: We analysed cross-sectional data from 2548 couples from the Centre for cArdio-metabolic Risk Reduction in South Asia cohort in Chennai, Delhi and Karachi. We estimated couple concordance in presence of ≥1 of diabetes, hypertension and dyslipidaemia (positive concordance: both spouses (W+H+); negative concordance: neither spouse (W-H-); discordant wife: only wife (W+H-); or discordant husband: only husband (W-H+)). We assessed associations of five socioeconomic and household characteristics, and six modifiable risk factors with couple concordance using multinomial logistic regression models with couples as the unit of analysis (reference: W-H-).Results: Of the couples, 59.4% (95% CI 57.4% to 61.3%) were concordant in chronic conditions (W+H+: 29.2% (95% CI 27.4% to 31.0%); W-H-: 30.2% (95% CI 28.4%- to 32.0%)); and 40.6% (95% CI 38.7% to 42.6%) discordant (W+H-: 13.1% (95% CI 11.8% to 14.4%); W-H+: 27.6% (95% CI 25.9% to 29.4%)). Compared with couples with no conditions (W-H-), couples had higher relative odds of both having at least one condition if they had higher versus lower levels of: income (OR 2.03 (95% CI 1.47 to 2.80)), wealth (OR 2.66 (95% CI 1.98 to 3.58)) and education (wives' education: OR 1.92 (95% CI 1.29 to 2.86); husbands' education: OR 2.98 (95% CI 1.92 to 4.66)) or weight status (overweight or obesity in both spouses ORs 7.17 (95% CI 4.99 to 10.30)).Conclusions: Positive couple concordance in major chronic conditions is high in urban India and Pakistan, especially among couples with relatively higher socioeconomic position. This suggests that prevention and management focusing on couples at high risk for concordant chronic conditions may be effective and more so in higher socioeconomic groups.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".