Two Mortality Estimates, Two Different Questions

Julianne Holt-Lunstad’s 2010 meta-analysis in PLoS Medicine is probably the single most cited number in this field: people with stronger social relationships had a 50% greater likelihood of survival over the follow-up period than those with weaker ones, pooled across 148 studies and 308,849 participants. Twelve years later, the American Heart Association’s 2022 scientific statement on social isolation and cardiovascular and brain health reported something that sounds like the same claim scaled down: roughly a 30% increased risk of heart attack, stroke, or death from either, associated with social isolation and loneliness. Specifically, 29% for heart attack and coronary death, 32% for stroke.

Fifty percent against thirty percent invites an obvious question: which one is right? The answer is that both are right, because they are not measuring the same thing, and treating them as competing estimates of a single underlying “risk of disconnection” is the mistake, not the numbers themselves.

Different outcomes, not different effect sizes

The 2010 figure is a survival estimate across all causes of death, over whatever follow-up period each of the 148 included studies used. It answers: given a fixed amount of time, is a person with weak social ties more or less likely to die, from anything, than a person with strong ties? The pooled effect is expressed as a likelihood-of-survival ratio, which is why it reads as a single dramatic number — comparable, Holt-Lunstad argued, to established risk factors like smoking or obesity.

The 2022 AHA statement asks a narrower question: among people with social isolation or loneliness, what is the additional risk of a specific cardiovascular event — heart attack, stroke, cardiovascular death — relative to people without it? That is a cause-specific hazard, not an all-cause survival ratio, and it is drawn from a different and smaller pool of studies designed to isolate cardiovascular endpoints rather than mortality from any source. A person can have an elevated all-cause mortality risk from social disconnection driven partly by suicide, respiratory illness, or accident, none of which show up in a cardiovascular-specific estimate at all. Comparing the two numbers is a bit like comparing “risk of dying from anything this decade” to “risk of a stroke specifically.” They can both be true, and there is no arithmetic reason the second number should be a fraction of the first.

Different denominators, different populations

The 148 studies underlying the 2010 estimate span a wide range of ages, health statuses, and countries, with study populations selected primarily on whether they measured social relationships and tracked mortality, not on cardiovascular risk. The AHA statement drew on a narrower literature purpose-built to examine cardiovascular and cerebrovascular outcomes, generally in populations already characterized by cardiovascular risk factors or events. A pooled estimate is only as comparable as its source population, and these are not the same population, sampled the same way, asking the same question.

This matters because the 2015 follow-up meta-analysis by Holt-Lunstad, published in Perspectives on Psychological Science, illustrates how sensitive these pooled numbers are to how the underlying construct is defined. That analysis separated social isolation, loneliness, and living alone into three distinct predictors of early mortality, with odds ratios of 1.29, 1.26, and 1.32 respectively. None of those numbers is 50%, and none is 30%. They are neither more nor less “correct” than either of the other two estimates; they are answering yet another version of the question, this time with isolation, loneliness, and living alone disaggregated rather than pooled into a single composite measure of “social connection,” which is what the 2010 analysis used.

Three credible meta-analytic efforts by overlapping authors, using overlapping but not identical source studies, produce three different headline numbers, because each one made a different decision about what counts as the exposure and what counts as the outcome. That is not evidence of sloppiness. It is what happens whenever multiple research teams — or the same team at different points — pool observational studies without a single shared operational definition of either variable, a gap the 2023 review in BMC Public Health on the state of loneliness and social isolation research names explicitly as a persistent barrier to comparing findings across studies.

What the AHA statement says about itself

The AHA statement is unusually candid about the limits of its own numbers. It identifies the absence of intervention evidence — trials that actually change someone’s degree of isolation and then measure cardiovascular outcomes — as the central research gap in the field. Every one of the risk ratios in the statement, including the 29% and 32% figures, comes from observational data: people who happened to be more isolated were compared to people who happened to be less isolated, and the difference in outcomes was measured after the fact. That design can establish association with a fair degree of confidence when the pooled sample is large, as it is here, but it cannot establish that reducing isolation would reduce cardiovascular risk by a corresponding amount. The 2010 mortality estimate carries the identical limitation: it is built entirely from cohorts observed over time, not from randomized manipulation of anyone’s social relationships.

What would resolve the apparent disagreement

Nothing about the discrepancy between 50% and 30% needs resolving in the sense of picking a winner. What would genuinely help is a shared reporting convention: state the outcome (all-cause mortality, cardiovascular death, a specific cause), the exposure as actually operationalized (a composite social-relationship score, isolation alone, loneliness alone, living arrangement), the population sampled, and the follow-up window, every time a headline percentage gets quoted outside its own paper. Readers encountering a “50% higher risk” claim and a “30% higher risk” claim in the same week reasonably conclude the field cannot agree on its own basic facts. The more accurate reading is that the field has produced several careful answers to several different, narrower questions, and the shorthand headline strips out exactly the information needed to tell them apart.

A genuinely comparable future study would hold the outcome fixed, use a single pre-registered definition of isolation and loneliness as distinct constructs, and report effect sizes as hazard ratios with confidence intervals rather than single percentage points detached from their denominators. Until then, the honest use of either number is to cite it for the specific claim it supports, and no further.