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Repair Windows errors before they cause bigger problemsFix Now →Scan for outdated or missing drivers - takes under a minuteDriver Scan →A 2026 study found that countries with more cats per 10,000 people tended to report higher happiness scores. The comparison covered 93 countries, but it does not show that individual cat owners are happier—or that cats cause happiness.
What the study found
In a peer-reviewed paper published in PLOS ONE on September 30, 2026, Javier I. Borráz-León, Markus J. Rantala, Indrikis Krams, and Dario Maestripieri analyzed country-level measures of cat density, happiness, Toxoplasma gondii seroprevalence, and socioeconomic conditions across 93 countries. They defined cat density as cats per 10,000 inhabitants. The authors reported a positive correlation between cat density and happiness: r=0.620, p<0.001, with a 95% confidence interval of 0.480–0.733. Read the study in PLOS ONE.
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That is a comparison of national averages and indicators—not a survey comparing cat owners with people who do not have cats. It describes a pattern in which countries with higher measured cat density also tended to have higher happiness scores; it cannot establish what any one person’s experience of having a cat is like.
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Happiness scores covered 2022–2024
The authors used scores from the World Population Review’s 2025 Happiest Countries report. The scores represent a three-year average for 2022–2024, not happiness measured in 2026. The report’s score draws on Gallup polling across six categories: GDP per capita, social support, healthy life expectancy, freedom to make life choices, generosity, and perceptions of internal and external corruption.
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Cat density is not a measure of the human-cat bond
A national count per 10,000 people does not reveal whether cats are pets, how they are cared for, or whether people have close and positive relationships with them. It is therefore an imperfect proxy for the kinds of human-animal interactions that might affect well-being.
How the cat result compares with other country-level patterns
Cat density was not the only national measure associated with happiness. Borráz-León and colleagues also reported positive bivariate correlations for income level, GDP, and health expenditure. The figures below are correlations reported in the 2026 study; they do not by themselves show that any one factor causes happiness.
| Country-level measure | Reported correlation with happiness |
|---|---|
| Cat density | r=0.620; p<0.001; 95% CI 0.480–0.733 |
| Income level | r=0.780; p<0.001; 95% CI 0.686–0.849 |
| GDP | r=0.800; p<0.001; 95% CI 0.718–0.866 |
| Health expenditure | r=0.350; p<0.001; 95% CI 0.162–0.521 |
These comparisons put the cat finding in context: it sits alongside strong associations with economic measures in the same country-level data. The correlations are not a ranking of causes, and they do not isolate the role of cat ownership in people’s lives.
What the adjusted analysis adds
The researchers also modeled happiness using cat density, health expenditure, and T. gondii IgM and IgG seroprevalence. The model’s R² was 0.470. In that analysis, cat density remained positively associated with happiness (β=0.520, p<0.001), while IgM seroprevalence was negatively associated (β=−0.240, p=0.021). Health expenditure and IgG were reported as small, non-significant predictors.
An adjusted association means the model considered the included measures together; it does not rule out other explanations. Wealth, living conditions, culture, attitudes toward pets, public health, and unmeasured differences between countries could contribute to the pattern. The paper also includes an exploratory statistical mediation analysis, which should not be read as proof of a causal sequence or mechanism.
What the parasite findings do—and do not—say
T. gondii is a parasite whose exposure the study examined using IgM and IgG seroprevalence. The underlying prevalence data came from studies of pregnant women, used as a proxy for exposure in the broader population. Pregnant women may not represent everyone in a country, so these figures cannot be treated as a direct measure of whole-population prevalence.
The authors reported a counterintuitive negative association between cat density and T. gondii seroprevalence. They suggest that cats in wealthier countries may more often be kept indoors, fed processed food, and receive routine medical care, while free-roaming cats may be more common in lower- and middle-income settings. That is a possible explanation offered by the authors, not a tested finding about why the association occurred.
Why the result is not proof that cats make people happier
- The unit of analysis is countries. A relationship between national averages cannot establish that an individual with a cat is happier than an otherwise similar person without one.
- The analysis is cross-sectional and exploratory. It compares country measures rather than tracking changes over time, so it cannot establish which factor came first.
- The measures are imperfect proxies. Cat density does not measure ownership or the quality of human-cat relationships, and the parasite data from pregnant women may not represent a whole population.
- Other national differences may matter. Economic conditions and many cultural, social, and public-health factors could influence the observed associations.
The authors report post-hoc power of 85% to detect a moderate correlation of r=0.3 with N=93 at α=0.05, while noting the study was underpowered to reliably detect small effects such as r<0.20. This describes the analysis’s stated ability to detect effects of different sizes; it does not turn the country-level correlations into causal evidence.
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What to take from the headline
The evidence supports a specific, limited conclusion: across 93 countries, higher cat density was associated with higher happiness scores for 2022–2024, and cat density remained positively associated with happiness in the study’s adjusted model. It does not establish that cats make individuals happier. As the authors put it, “These results underscore a complex and yet understudied relationship between human-animal interactions, infectious disease ecology, and national well-being.”
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