BackgroundSocial isolation, defined as an individual’s lack of social connections, is particularly prevalent among older adults. However, its association with health outcomes among the oldest-old population (aged 80 and above) was understudied.AimsTo examine the association between social isolation and the likelihood of becoming a centenarian among the oldest-old people in China, aiming to provide novel insights into promoting healthy aging and longevity.MethodsUsing data from The Chinese Longitudinal Healthy Longevity Survey, conducted in 22 provinces in mainland China since 1998, we performed a community-based, prospective nested case-control study. The primary outcome was survival to the age of 100 by 2018 (the end of follow-up). Information on social isolation and other covariates was collected via a questionnaire at baseline. The degree of social isolation was categorized as low, moderate, and high. Included (n = 5,716) were 1,584 identified centenarians and 4,132 controls (deceased before reaching 100 years), matched by age, sex, and year of entry. A conditional logistic regression model was used to evaluate the association between social isolation and the likelihood of becoming a centenarian, adjusting for demographic factors, lifestyle factors, chronic disease, potential disability, optimistic attitude, and perceived loneliness.ResultsIndividuals with the highest social isolation score had lower odds of becoming centenarians (adjusted OR:0.82; 95% CI: 0.68, 0.98), relative to those with the least social isolation (P-value < 0.05), and this association persisted in sensitivity analyses. The association was more pronounced among ever smokers, compared to never smokers (P-value = 0.001). We did not observe significant interactions between social isolation and other covariates (P-value > 0.05 for all).ConclusionsThis study highlights the inverse association between social isolation and the likelihood of becoming a centenarian, emphasizing the need for public health initiatives to combat isolation in the older population.
Read full abstract