What Did the 1979 Alameda County Study Count When It Counted Your Friends?

The 1979 Alameda County paper is the study that put a number on being alone. Lisa Berkman and S. Leonard Syme found that adults with the fewest social and community ties were more likely to die over nine years than adults with the most. Compared with the most connected, the most isolated had age-adjusted relative risks of 2.3 for men and 2.8 for women.

Many later articles on friendship and longevity trace back to it, directly or through a meta-analysis, so what the researchers counted matters.

The 1965 survey

In 1965 the Human Population Laboratory surveyed a random sample of 6,928 adults in Alameda County, California. Berkman and Syme then used mortality records to see who had died by the end of the next nine years, and asked whether the answers people gave in 1965 predicted it. The analyzed sample was smaller than the 6,928 surveyed, since not every respondent had complete data; the paper’s own tables give the exact count.

What the index counted

The index combined four kinds of connection:

1. Marriage.
2. Contacts with close friends and relatives.
3. Church membership.
4. Membership in other groups and associations.

What the index leaves out is telling. Nobody was asked whether their friends were kind, whether they felt understood or whether they were lonely. The index counted the structure of a life: who you were married to, how often you saw people, which rooms you walked into on a regular basis.

The mortality results

People with fewer ties died more. The gradient did not come from health habits alone: the association held after the authors adjusted for self-reported health in 1965, year of death, socioeconomic status, smoking, alcohol, obesity, physical activity, use of preventive health services and a cumulative index of health practices.

Seeman and colleagues later followed the same cohort for 17 years (American Journal of Epidemiology, 1987). Ties still predicted survival, including for people 70 and older, with a relative hazard of 1.49 for the Social Network Index. Marital status mattered most for people under 60. After 60, contact with close friends and relatives carried more of the weight.

Holt-Lunstad’s meta-analyses

Julianne Holt-Lunstad’s 2010 meta-analysis in PLOS Medicine pooled 148 studies and 308,849 participants and reported an odds ratio of 1.50 (95% CI 1.42 to 1.59) for survival among people with stronger relationships. Berkman and Syme appear in its list of included studies. Her 2015 paper in Perspectives on Psychological Science split the question by type and reported 29% higher likelihood of mortality for social isolation, 26% for loneliness and 32% for living alone.

The 1979 paper is the origin point, and the meta-analyses are what made it hard to wave away. Alameda County is one cohort in one county in one decade. By 2010 the same direction of effect had turned up across many countries and measures. The Roseto effect is a related town-level story.

Limits

The study is observational. A person already unwell in 1965 might see fewer people and also be closer to dying, and baseline health adjustment only partly handles that. The index also counts presence, not quality, so a tense marriage and a warm one score the same. And it describes a 1965 county, where church and club membership meant something different than it does now.

What the index rewarded

The index rewarded contact that recurs and belongs to a structure. Marriage is a standing arrangement. So is a congregation, or a weekly club meeting. None of those depends on someone remembering to text.

That reading is an inference from what the index counted, not something the paper tested. A recurring friend date is the small-scale version, and Dunbar’s layers are one way to decide which handful of people get the regular slots.

What Alameda County supports is modest: after the adjustments listed above, the 1965 respondents with more places to be among other people were more likely to be alive nine years later.