Abstract
OBJECTIVES: Happiness has been shown to influence many health-related outcomes in older adults. Identifying correlates and brain substrates of happiness across countries and cultures is an important goal, as the global older adult population continues to increase. METHODS: We used univariate and multiple regression to examine associations between happiness and several demographic, health, and lifestyle variables in 665 older adults (39% female) from Kerala, India. We also used Bayesian regression to examine associations between cortical thickness and happiness in a subsample of 188 participants that completed MRI scanning. RESULTS: Happiness was significantly associated with several variables. In our multiple regression model, which included all significant univariate predictors, self-rated health, depression, anxiety, apathy, social network size, social network diversity, and social support significantly predicted happiness. Demographic indicators (age, sex, education, marital status, residence, and employment status/type), cognitive impairment, comorbidities, and leisure activities were not significantly associated with happiness in the multiple regression model. Cortical thickness in several brain regions was positively associated with happiness scores, including frontal, temporal, parietal, occipital, and cingulate regions. DISCUSSION: Understanding the key correlates is critical for identifying both modifiable factors that can be targeted in well-being interventions and fixed characteristics that identify those at-risk for reduced happiness. The widespread pattern of brain regions associated with happiness is consistent with the multifactorial nature of happiness and, given that the regions identified do not overlap with those vulnerable to cortical thinning, can help explain why subjective well-being, unlike other cognitive functions, is largely resistant to age-related decline.