Summary:A new study debunked the myth that “opposites attract,” revealing that similarity is more common in partnerships. Analyzing over 130 traits across millions of couples from the past century, between 82% and 89% of traits showed partners were likely to be alike.
Only in a small fraction did individuals partner with those different from them. This research not only reshapes our understanding of human relationships but has implications for genetic research, highlighting the flaws in assuming random human mating.
Key Facts:
- An extensive analysis covering more than 130 traits found that for 82%-89% of them, partners were likely to be similar, challenging the “opposites attract” notion.
- While most traits showed a positive correlation in partners, a few like chronotype, tendency to worry, and hearing difficulty showed a small negative correlation.
- The findings can significantly impact genetic research, emphasizing that “assortative mating” (similar traits pairing up) can influence genetic study results.
Source: University of Colorado
Opposites don’t actually attract.
That’s the takeaway from a sweeping CU Boulder analysis of more than 130 traits and including millions of couples over more than a century.
“Our findings demonstrate that birds of a feather are indeed more likely to flock together,” said first author Tanya Horwitz, a doctoral candidate in the Department of Psychology and Neuroscience and the Institute for Behavioral Genetics (IBG).
The study, published Aug. 31 in the journal Nature Human Behaviour, confirms what individual studies have hinted at for decades, defying the age-old adage that “opposites attract.”
It found that for between 82% and 89% of traits analyzed—ranging from political leanings to age of first intercourse to substance use habits—partners were more likely than not to be similar.
For only 3% of traits, and only in one part of their analysis, did individuals tend to partner with those who were different than them.
Aside from shedding light on unseen forces that may shape human relationships, the research has important implications for the field of genetic research.
“A lot of models in genetics assume that human mating is random. This study shows this assumption is probably wrong,” said senior author and IBG Director Matt Keller, noting that what is known as “assortative mating”—when individuals with similar traits couple up—can skew findings of genetic studies.
Looking back more than a century
For the new paper, the authors conducted both a review, or meta-analysis, of previous research and their own original data analysis.
For the meta-analysis, they looked at 22 traits across 199 studies including millions of male-female co-parents, engaged pairs, married pairs or cohabitating pairs. The oldest study was conducted in 1903.
In addition, they used a dataset called the UK Biobank to study 133 traits, including many that are seldom studied, across almost 80,000 opposite-sex pairs in the United Kingdom.
Same sex couples were not included in the research. Because the patterns there may differ significantly, the authors are now exploring those separately.
Across both analyses, traits like political and religious attitudes, level of education, and certain measures of IQ showed particularly high correlations. For instance, on a scale in which zero means there is no correlation and 1 means couples always share the trait, the correlation for political values was .58.
Traits around substance use also showed high correlations, with heavy smokers, heavy drinkers and teetotalers tending strongly to partner up with those with similar habits.
Meanwhile, traits like height and weight, medical conditions and personality traits showed far lower but still positive correlations. For instance, the correlation for neurotocism was .11.
For some traits, like extroversion, there was not much of a correlation at all.
“People have all these theories that extroverts like introverts or extroverts like other extroverts, but the fact of the matter is that it’s about like flipping a coin: Extroverts are similarly likely to end up with extroverts as with introverts,” said Horwitz.
Rarely, opposites may attract
In the meta-analysis, the researchers found “no compelling evidence” on any trait that opposites attract. In the UK Biobank sample, they did find a handful of traits in which there seemed to be a negative correlation, albeit small.
Those included: chronotype (whether someone is a “morning lark” or “night owl”), tendency to worry and hearing difficulty.
More research must be done to unpack those findings, they said.
The trait for which couples were most likely to be similar was, not surprisingly, birth year.
But even seldom-studied traits, like how many sexual partners a person had had or whether they had been breastfed as a child, showed some correlation.
“These findings suggest that even in situations where we feel like we have a choice about our relationships, there may be mechanisms happening behind the scenes of which we aren’t fully aware,” said Horwitz.
Next-generation implications
The authors note that couples share traits for a variety of reasons: Some grow up in the same area. Some are attracted to people who are similar to them. Some grow more similar the longer they are together.
Depending on the cause, there could be downstream consequences.
For example, Horwitz explains, if short people are more likely to produce offspring with short people and tall people with tall people, there could be more people at the height extremes in the next generation. The same goes for psychiatric, medical or other traits.
There could also be social implications.
For instance, some small previous studies have suggested that people in the U.S. are growing more likely to couple up with people with similar educational backgrounds—a trend that, some theorize, could widen the socioeconomic divide.
Notably, the new study also showed that the strength of correlations for traits differed across populations. They likely also change over time, the authors suspect.
The researchers caution that the correlations they found were fairly modest and should not be overstated or misused to promote an agenda (Horwitz points out that assortative mating research was, tragically, co-opted by the eugenics movement).
They do hope the study will spark more research across disciplines, from economics to sociology to anthropology and psychology.
“We’re hoping people can use this data to do their own analyses and learn more about how and why people end up in the relationships they do,” she said.
About this attraction and psychology research news
Author: Lisa Marshall
Source: University of Colorado
Contact: Lisa Marshall – University of Colorado
Image: The image is credited to Neuroscience News
Original Research: Closed access.
“Evidence of correlations between human partners based on systematic reviews and meta-analyses of 22 traits and UK Biobank analysis of 133 traits” by Tanya Horwitz et al. Nature Human Behavior
Abstract
Evidence of correlations between human partners based on systematic reviews and meta-analyses of 22 traits and UK Biobank analysis of 133 traits
Positive correlations between mates can increase trait variation and prevalence, as well as bias estimates from genetically informed study designs.
While past studies of similarity between human mating partners have largely found evidence of positive correlations, to our knowledge, no formal meta-analysis has examined human partner correlations across multiple categories of traits.
Thus, we conducted systematic reviews and random-effects meta-analyses of human male–female partner correlations across 22 traits commonly studied by psychologists, economists, sociologists, anthropologists, epidemiologists and geneticists.
Using ScienceDirect, PubMed and Google Scholar, we incorporated 480 partner correlations from 199 peer-reviewed studies of co-parents, engaged pairs, married pairs and/or cohabitating pairs that were published on or before 16 August 2022. We also calculated 133 trait correlations using up to 79,074 male–female couples in the UK Biobank (UKB).
Estimates of the 22 mean meta-analysed correlations ranged from rmeta = 0.08 (adjusted 95% CI = 0.03, 0.13) for extraversion to rmeta = 0.58 (adjusted 95% CI = 0.50, 0.64) for political values, with funnel plots showing little evidence of publication bias across traits.
The 133 UKB correlations ranged from rUKB = −0.18 (adjusted 95% CI = −0.20, −0.16) for chronotype (being a ‘morning’ or ‘evening’ person) to rUKB = 0.87 (adjusted 95% CI = 0.86, 0.87) for birth year.
Across analyses, political and religious attitudes, educational attainment and some substance use traits showed the highest correlations, while psychological (that is, psychiatric/personality) and anthropometric traits generally yielded lower but positive correlations.
We observed high levels of between-sample heterogeneity for most meta-analysed traits, probably because of both systematic differences between samples and true differences in partner correlations across populations.
