With advances in natural language processing and machine learning, researchers are leveraging social media as a low-cost, low-burden method for measuring various psychosocial factors. However, it is unclear whether information derived from social media is generalizable to broader populations, especially middle-aged and older adults. Using data on women aged 53-70 years from Nurses Health Study II (2017-2018; n = 49,045), we assessed differences in sociodemographic characteristics, health conditions, behaviors, and psychosocial factors between regular and nonregular users of Facebook (Facebook, Inc., Menlo Park, California). We evaluated effect sizes with phi (φ) coefficients (categorical data) or Cohens d (continuous data) and calculated odds ratios with 95% confidence intervals. While most comparisons between regular and nonregular users achieved statistical significance in this large sample, effect sizes were mostly very small (conventionally defined as φ or d <0.01) (e.g., optimism score: meanregular users = 19 vs. meannonregular users = 19 (d = -0.03); physical activity: meanregular users = 24 metabolic equivalent of task (MET)-hours/week vs. meannonregular users = 24 MET-hours/week (d = 0.01)). Some factors had slightly larger differences for regular users versus nonregular users (e.g., depression: 28% vs. 23% (φ = 0.05); odds ratio = 1.27 (95% confidence interval: 1.22, 1.33); obesity: 34% vs. 26% (φ = 0.07); odds ratio = 1.42 (95% confidence interval: 1.36, 1.48)). Results suggest that regular Facebook users were similar to nonregular users across sociodemographic and psychosocial factors, with modestly worse health regarding obesity and depressive symptoms. In future research, investigators should evaluate other demographic groups.

Greater levels of psychological well-being are associated with reduced disease and mortality risk, and lifestyle habits may be potential mechanisms underlying these relationships. Prospective studies show that positive psychological factors enhance the likelihood of adopting specific health behaviors; yet, whether they promote the adoption of multiple healthy behaviors, which can have a multiplicative effect on disease and mortality risk compared to individual behaviors, is unknown. We investigated whether happiness and optimism were related to a healthy lifestyle (characterized by multiple health behaviors) over 10-22 years of follow-up; we also explored bidirectional associations, assessing if a healthy lifestyle at baseline was related to greater likelihood of experiencing higher happiness and optimism over time. Women reported levels of happiness in 1992 (N = 52,133) and optimism in 2004 (N = 36,802). Health-related behaviors (physical activity, body mass index, diet, alcohol and tobacco consumption) were self-reported and combined into a lifestyle score, every four years from baseline until 2014. Multivariable generalized estimating equations with a Poisson distribution were used. Women with moderate and higher (versus lower) happiness levels were more likely to report sustaining healthy lifestyles (RR = 1.18, CI = 1.11-1.25; RR = 1.39, CI = 1.32-1.46, respectively). In secondary analyses, the magnitude of the inverse association was somewhat smaller (likelihood of sustaining higher happiness levels for baseline healthy versus unhealthy lifestyle, RR = 1.11, CI = 1.10-1.12). Results were similar when considering optimism as the exposure and in other secondary analyses (e.g., across individual habits). While bidirectional associations are apparent, these findings suggest pursuing happiness and optimism as modifiable determinants of lifestyle deserves further consideration.

Most research on exceptional longevity has investigated biomedical factors associated with survival, but recent work suggests nonbiological factors are also important. Thus, we tested whether higher optimism was associated with longer life span and greater likelihood of exceptional longevity. Data are from 2 cohorts, women from the Nurses Health Study (NHS) and men from the Veterans Affairs Normative Aging Study (NAS), with follow-up of 10 y (2004 to 2014) and 30 y (1986 to 2016), respectively. Optimism was assessed using the Life Orientation Test-Revised in NHS and the Revised Optimism-Pessimism Scale from the Minnesota Multiphasic Personality Inventory-2 in NAS. Exceptional longevity was defined as survival to age 85 or older. Primary analyses used accelerated failure time models to assess differences in life span associated with optimism; models adjusted for demographic confounders and health conditions, and subsequently considered the role of health behaviors. Further analyses used logistic regression to evaluate the likelihood of exceptional longevity. In both sexes, we found a dose-dependent association of higher optimism levels at baseline with increased longevity (P trend < 0.01). For example, adjusting for demographics and health conditions, women in the highest versus lowest optimism quartile had 14.9% (95% confidence interval, 11.9 to 18.0) longer life span. Findings were similar in men. Participants with highest versus lowest optimism levels had 1.5 (women) and 1.7 (men) greater odds of surviving to age 85; these relationships were maintained after adjusting for health behaviors. Given work indicating optimism is modifiable, these findings suggest optimism may provide a valuable target to test for strategies to promote longevity.