As population aging is progressing at an unprecedented speed worldwide, the transition to a super-aged society has become a key agenda at the national level.

Beyond simply extending life expectancy, achieving “active and healthy aging” has emerged as one of the greatest challenges in health and social welfare. In this context, researchers and practitioners have identified “social isolation” and “loneliness” as two of the most critical threats facing the older population. (Hussain et al., 2023)

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In the past, many studies and policies addressing aging issues focused on older adults’ demographic characteristics — such as age, income, and the presence of chronic disease — or on simple contact frequency based on subjective surveys. For example, they attempted to identify at-risk groups for isolation through fragmentary questions such as, “How many times a week do you meet acquaintances?” or “Do you live with family members?”

These traditional approaches have a fundamental limitation in capturing the complex and dynamic interactions underlying human relationships.

Some people enjoy a high level of psychological stability through a deep and dense relationship with just one acquaintance, while others interact superficially with many people yet still feel lonely in a crowd.

In addition, transitional life events in old age — such as retirement, bereavement, children becoming independent, and residential relocation — alter the structure of the relationships individuals have formed within their communities.

Social network analysis (SNA) focuses on this very point.

It goes beyond asking, “Who is connected to whom?” and seeks deeper, scientific answers about how the density of those ties and the shape of their branching structure causally affect older adults’ cognitive functioning, depression, and even mortality. (Schutter et al., 2022)

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