Death following partner bereavement: a self-controlled case series analysis

Michael King, Rebecca Lodwick, Rebecca Jones, Heather Whitaker, Irene Petersen

Research output: Contribution to journalArticlepeer-review

31 Downloads (Pure)

Abstract

Background - There is mixed evidence that older people bereaved of a spouse or partner are at risk of adverse outcomes. The main difficulty is to take account of other explanatory factors. We tested for an association between a patient's death and the timing of any bereavement of a cohabitee.

Method - Self-controlled case series study in which each case serves as his or her own control and which thereby accounts for all fixed measurable and unmeasurable confounders. We used the Health Improvement Network (THIN) primary care database to identify patients who died aged 50±99 years during the period 2003 to 2014. We used the household identifier in the database to determine whether they had an opposite sex cohabitee at the start of the observation period.

Results - 38,773 men and 23,396 women who had died and who had a cohabitee at the start of the observation period, were identified and included in male and female cohorts respectively. A higher risk of death was found in the 24 months after the death of the cohabitee than in the time classified as unexposed. The greatest risk was during the first 3 months after the death of the cohabitee (age-adjusted incidence rate ratio [IRR] 1.63, 95% CI 1.45-1.83 in the male cohort, and IRR 1.70, 95% CI 1.52-1.90 in the female cohort).

Conclusion - Risk of death in men or women was significantly higher after the death of a cohabitee and this was greatest in the first three months of bereavement. We need more evidence on the effectiveness of interventions to reduce this increased mortality.

Original languageEnglish
Article numbere0173870
JournalPLoS One
Volume12
Issue number3
DOIs
Publication statusPublished - 15 Mar 2017
Externally publishedYes

Fingerprint

Dive into the research topics of 'Death following partner bereavement: a self-controlled case series analysis'. Together they form a unique fingerprint.

Cite this