Researchers identify the optimal dose of urban greenness for boosting mental well-being

A new analysis suggests that when it comes to the mental health benefits of urban green spaces, a moderate amount is best. The research, which synthesized four decades of studies, found that the relationship between the quantity of greenery and mental well-being follows an inverted U-shaped pattern, where benefits decline after a certain point. This finding challenges the simpler idea that more green space is always better and was published in the journal Nature Cities.

Researchers have long established a connection between exposure to nature and improved mental health for city dwellers. However, the exact nature of this relationship has been unclear. Bin Jiang, Jiali Li, and a team of international collaborators recognized a growing problem in the field. Early studies often suggested a straightforward linear connection, implying that any increase in greenness would lead to better mental health outcomes. This made it difficult for city planners to determine how much green space was optimal for public well-being.

More recent studies started to show curved, non-linear patterns, but because they used different methods and were conducted in various contexts, the evidence remained fragmented and inconclusive. Without a clear, general understanding of this dose-response relationship, urban planners and policymakers lack the scientific guidance needed to allocate land and resources to maximize mental health benefits for residents. The team aimed to resolve this by searching for a generalized pattern across the entire body of existing research.

To achieve their goal, the scientists conducted a meta-analysis, a type of study that statistically combines the results of many previous independent studies. Their first step was a systematic search of major scientific databases for all empirical studies published between 1985 and 2025 that examined the link between a measured “dose” of greenness and mental health responses. This exhaustive search initially identified over 128,000 potential articles. The researchers then applied a strict set of criteria to filter this large pool, narrowing it down to 133 studies that directly measured a quantitative relationship between greenness and mental health outcomes like stress, anxiety, depression, or cognitive function.

From this collection of 133 studies, the team focused on a subset of 69 that measured the “intensity” of greenness, as this was the most commonly studied variable and provided enough data for a robust analysis. They further divided these studies into two categories based on how greenness was measured. The first category was “eye-level greenness,” which captures the amount of vegetation a person sees from a ground-level perspective, such as when walking down a street. The second was “top-down greenness,” which is measured from aerial or satellite imagery and typically represents the percentage of an area covered by tree canopy or other vegetation.

A significant challenge in combining so many different studies is that they use various scales and metrics. To address this, the researchers standardized the data. They converted the mental health outcomes from all studies onto a common scale ranging from negative one to one. They also re-analyzed images from the original papers to calculate the percentage of greenness in a consistent way across all studies. After standardizing the data, they extracted representative points from each study’s reported dose-response curve and combined them into two large datasets, one for eye-level greenness and one for top-down greenness.

With all the data points compiled and standardized, the researchers performed a curve-fitting analysis. They tested several mathematical models, including a straight line (linear model), a power-law curve, and a quadratic model, which produces an inverted U-shape. The results showed that for both eye-level and top-down greenness, the quadratic model was the best fit for the collective data. This indicates that as the amount of greenness increases from zero, mental health benefits rise, reach a peak at a moderate level, and then begin to decline as the amount of greenness becomes very high.

The analysis identified specific thresholds for these effects. For eye-level greenness, the peak mental health benefit occurred at 53.1 percent greenness. The range considered “highly beneficial,” representing the top five percent of positive effects, was between 46.2 and 59.5 percent. Any positive effect, which the researchers termed a “non-adverse effect,” was observed in a broader range from 25.3 to 80.2 percent. Outside of this range, at very low or very high levels of eye-level greenness, the effects were associated with negative mental health responses.

The findings for top-down greenness were similar. The optimal dose for the best effect was found to be 51.2 percent. The highly beneficial range was between 43.1 and 59.2 percent, and the non-adverse range spanned from 21.1 to 81.7 percent. These specific figures provide practical guidance for urban design, suggesting target percentages for vegetation cover that could yield the greatest psychological rewards for communities.

The researchers propose several reasons why this inverted U-shaped pattern exists. At very low levels of greenness, an environment can feel barren or desolate, which may increase feelings of stress or anxiety. As greenery is introduced, the environment becomes more restorative.

However, at extremely high levels of greenness, a landscape can become too dense. This might reduce natural light, obstruct views, and create a feeling of being closed-in or unsafe, potentially leading to anxiety or a sense of unease. A dense, complex environment may also require more mental effort to process, leading to cognitive fatigue rather than restoration. A moderate dose appears to strike a balance, offering nature’s restorative qualities without becoming overwhelming or threatening.

The study’s authors acknowledge some limitations. By combining many diverse studies, some nuance is lost, as different populations, cultures, and types of mental health measures are grouped together. The analysis was also limited to the intensity of greenness; there was not enough consistent data available to perform a similar analysis on the frequency or duration of visits to green spaces, which are also important factors.

Additionally, very few of the original studies examined environments with extremely high levels of greenness, so the downward slope of the curve at the highest end is based more on statistical prediction than on a large volume of direct observation.

Future research could build on this foundation by investigating these other dimensions of nature exposure, such as the duration of visits or the biodiversity within green spaces. More studies are also needed that specifically test the effects of very high doses of greenness to confirm the predicted decline in benefits. Expanding this work to differentiate between types of vegetation, like trees versus shrubs or manicured parks versus wilder areas, could provide even more refined guidance for urban planning.

Despite these limitations, this comprehensive analysis provides a new, evidence-based framework for understanding how to design healthier cities, suggesting that the goal should not simply be to maximize greenness, but to optimize it.

The study, “A generalized relationship between dose of greenness and mental health response,” was authored by Bin Jiang, Jiali Li, Peng Gong, Chris Webster, Gunter Schumann, Xueming Liu, and Pongsakorn Suppakittpaisarn.