Background: Greenness, referring to a measurement of the density of vegetated land (e.g., gardens, parks, grasslands), has been linked with many human health outcomes. However, the evidence on greenness exposure and human microbiota remains limited, inconclusive, drawn from specific regions, and based on only modest sample size.
Objectives: We aimed to study the association between greenness exposure and human microbial diversity and composition in a large sample across 34 countries and regions.
Methods: We explored associations between residential greenness and human microbial alpha-diversity, composition, and genus abundance using data from 34 countries. Greenness exposure was assessed using the normalized difference vegetation index and the enhanced vegetation index mean values in the month before sampling. We used linear regression models to estimate the association between greenness and microbial alpha-diversity and tested the effect modification of age, sex, climate zone, and pet ownership of participants. Differences in microbial composition were tested by permutational multivariate analysis of variance based on Bray-Curtis distance and differential taxa were detected using the DESeq2 R package between two greenness exposure groups split by median values of greenness.
Results: We found that higher greenness was significantly associated with greater richness levels in the palm and gut microbiota but decreased evenness in the gut microbiota. Pet ownership and climate zone modified some associations between greenness and alpha-diversity. Palm and gut microbial composition at the genus level also varied by greenness. Higher abundances of the genera Lactobacillus and Bifidobacterium, and lower abundances of the genera Anaerotruncus and Streptococcus, were observed in people with higher greenness levels.
Discussion: These findings suggest that residential greenness was associated with microbial richness and composition in the human skin and gut samples, collected across different geographic contexts. Future studies may validate the observed associations and determine whether they correspond to improvements in human health. https://doi.org/10.1289/EHP12186.