Death of a loved one: Prevalence, risk, and protective factors for prolonged grief disorder - Bereavement is highly prevalent among older adults, a rapidly growing demographic of the US population that is projected to double by 2050. Estimates suggest that 3%- 10% of bereaved adults experience clinically significant levels of prolonged grief disorder (PGD), with older adults at higher risk. Recognition, prevention, and effective treatment of PGD is critical to reduce excess mortality among older adults, yet the capacity to identify and refer cases has lagged because PGD has not historically been included in the major psychiatric diagnostic manuals until the most recent editions of the Diagnostic and Statistical Manual of Mental Disorders 5th Edition Text Revision (DSM-5-TR) and International Classification of Diseases 11th Revision (ICD-11). As a result, it is only now possible to fill the historical knowledge gap around the prevalence and risk/protective factors for this highly impairing condition. The long-term goal of our work is to ascertain and validate PGD case status among older adults enrolled in an ongoing longitudinal study and identify modifiable factors that improve health outcomes for at-risk people. The central aim of this proposal is to use the unparalleled epidemiological resources of three >30-year longitudinal studies to characterize prevalent PGD consistent with newly introduced criteria in the DSM-5-TR for the first time in an ongoing cohort with exceptionally high response rates. First, we will ascertain probable PGD case status among 91,630 older adults with >30 years of prospective longitudinal data in the Nurses’ Health Study (NHS), NHS II, and Health Professionals Follow-Up Study (HPFS) and validate PGD case status among a randomly sampled bereaved subcohort of 27,115 adults. We will test apriori hypotheses regarding prevalence: a) PGD increases with age; b) After adjusting for sex differences in survival via inverse probability of censoring weighting, the prevalence of PGD does not meaningfully differ by sex; and c) Inclusion of sex and age in models will improve accuracy, as quantified using the mean absolute difference metric of model adequacy. Second, we will harness a novel data science approach to identify risk factors associated with PGD based on more than 30 years of prospective longitudinal data spanning biomarkers, genetics, psychosocial variables, and prior psychiatric history. Third, using a similar analytic approach, we will identify protective factors guided by the NIH Common Fund-supported Science of Behavior Change framework associated with reduced risk for PGD. Impact: The recent inclusion of PGD as a diagnostic category in the DSM-5-TR and ICD-11 affords healthcare professionals an infrastructure to identify and mobilize targeted bereavement-related services. The proposed project will address a gap in our understanding of PGD among older adults, thus advancing NIMH Strategic Goal 2: Charting mental illness trajectories to determine when, where, and how to intervene. Results will deliver insights into risk and protective factors that can inform targeted primary prevention efforts for the millions of older adults currently at risk of PGD.
