A simple snapshot assessment and some scoring of an individual's (entire, self-reported!) social life is too simplistic. The measurements would have to be performed throughout the life of each participant with sufficiently high frequency.
Why it happens is less clear. It could be stress effects, or it could be something like people with more social support are more likely to get help going in for preventative care etc.
So the finding here is that healthy, wealthy people with a support network age just like healthy, wealthy people with a support network.
> All models adjusted for demographic and socioeconomic variables selected a priori for their potential to confound associations between CSA and biological aging indicators. Covariates included age (in years), sex (male vs. female), race/ethnicity (White, Black, Other), educational attainment (12-point ordinal scale), and log-transformed current household income (USD). These variables were treated as exogenous predictors—assumed to temporally precede both CSA and biological outcomes—and were included to block potential backdoor paths and minimize bias.
> [...]
> Educational attainment and income reflect stratified access to material and psychosocial resources that affect both health behavior and biological risk processes (Adler and Newman, 2002). Treating these covariates as exogenous minimizes bias due to confounding while avoiding over-adjustment for potential mediators or introducing collider bias (Schisterman et al., 2009).
that's kind of interesting, though very far from the causal claims in the university press release.