What Matters and What Matters Most for Survival After age 80? A Multidisciplinary Exploration Based on Twin Data - Johansson, Boo; Thorvaldsson, Valgeir (Frontiers in Psychology, 2021)
Given research and public interest for conditions related to an extended lifespan, we addressed the questions of what matters and what matters most for subsequent survival past age 80. The data was drawn from the population-based and multidisciplinary Swedish OCTO Twin Study, in which a sample (N = 699) consisting of identical and same-sex fraternal twin pairs, followed from age 80 until death, provided detailed data on health, physical functioning, life style, personality, and sociodemographic conditions. Information concerning date of birth and death were obtained from population census register. We estimated heritability using an ACE model and evaluated the role of multiple predictors for the mortality-related hazard rate using Cox regression. Our findings confirmed a low heritability of 12%. As expected, longer survival was associated with being a female, an apolipoprotein E (APOE) e4 allele non-carrier, and a non-smoker. Several diseases were found to be associated with shorter survival (cerebrovascular, dementia, Parkinson’s, and diabetes) as well as certain health conditions (high diastolic blood pressure, low body mass index, and hip fracture). Stronger grip and better lung function, as well as better vision (but not hearing), and better cognitive function (self-evaluated and measured) was related to longer survival. Social embeddedness, better self-evaluated health, and life-satisfaction were also significantly associated with longer survival. After controlling for the impact of comorbidity, functional markers, and personality-related predictors, we found that sex, cerebrovascular diseases, compromised cognitive functioning, self-related health, and life-satisfaction remained as strong predictors. Cancer was only associated with the mortality hazard when accounting for other co-morbidities. The survival estimates were mostly in anticipated directions and contained effect sizes within the expected range. Noteworthy, we found that some of the so-called “soft-markers” remained strong predictors, despite a control for other factors. For example, self-evaluation of health and ratings of life-satisfaction provide additional and valuable information.