Gratitude and Mortality Among Older US Female Nurses
Bibliographic record
Abstract
Importance: Supporting healthy aging is a US public health priority, and gratitude is a potentially modifiable psychological factor that may enhance health and well-being in older adults. However, the association between gratitude and mortality has not been studied. Objective: To examine the association of gratitude with all-cause and cause-specific mortality in later life. Design, Setting, and Participants: This population-based prospective cohort study used data from self-reported questionnaires and medical records of 49 275 US older female registered nurses who participated in the Nurses' Health Study (2016 questionnaire wave to December 2019). Cox proportional hazards regression models estimated the hazard ratio (HR) of deaths by self-reported levels of gratitude at baseline. These models adjusted for baseline sociodemographic characteristics, social participation, physical health, lifestyle factors, cognitive function, and mental health. Data analysis was conducted from December 2022 to April 2024. Exposure: Gratitude was assessed with the 6-item Gratitude Questionnaire, a validated and widely used measure of one's tendency to experience grateful affect. Main Outcomes and Measures: Deaths were identified from the National Death Index, state statistics records, reports by next of kin, and the postal system. Causes of death were ascertained by physicians through reviewing death certificates and medical records. Results: Among the 49 275 participants (all female; mean [SD] age at baseline, 79 [6.16] years), 4608 incident deaths were identified over 151 496 person-years of follow-up. Greater gratitude at baseline was associated with a lower hazard of mortality in a monotonic fashion. For instance, the highest tertile of gratitude, compared with the lowest tertile, was associated with a lower hazard of all-cause deaths (HR, 0.91; 95% CI, 0.84-0.99) after adjusting for baseline sociodemographic characteristics, social participation, religious involvement, physical health, lifestyle factors, cognitive function, and mental health. When considering cause-specific deaths, death from cardiovascular disease was inversely associated with gratitude (HR, 0.85; 95% CI, 0.73-0.995). Conclusions and Relevance: This study provides the first empirical evidence suggesting that experiencing grateful affect is associated with increased longevity among older adults. The findings will need to be replicated in future studies with more representative samples.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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".