Environmental research · 2026
Environmental Factors Associated with Long COVID Severity: A Lifelines Cohort Analysis.
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Holtjer J C S, Thio C H L, Bloemsma L D, Maitland-Van der Zee A H, Downward G S, Vermeulen R C H, Lifelines Corona Research Initiative
Аннотация
BACKGROUND: Environmental components of the external exposome may influence the severity of long COVID, but population-based studies integrating multiple exposures remain scarce.
OBJECTIVES: To identify specific environmental factors most strongly associated with long COVID severity, measured as fatigue, quality of life (QoL), and number of symptoms, within a population-based sample of individuals with self-reported long COVID, and to compare results across multiple statistical approaches.
METHODS: We analyzed data from 1,108 participants in the Lifelines COVID-19 cohort who had self-reported long COVID and had complete covariate information. Outcome information was obtained through questionnaires, and environmental exposures were estimated by geocoded linkage to participant's residential addresses. Analyses were stratified by sex due to large differences in outcome distribution. Exposure-outcome associations were estimated using traditional regression models, horseshoe regression, Bayesian Model Averaging, and Random Forest, with adjustment for age, BMI, and education level. In secondary analyses we further stratified for urbanicity and severity of complaints.
RESULTS: Findings varied across analytical methods. The most consistent associations were observed in men: higher neighborhood prevalence of low-income residents was associated with greater fatigue, represented by lower scores (B=-2.09), and greater distance to blue space was associated with lower QoL, represented by higher scores (B=0.26). We did not find any associations in females, or the number of present symptoms in either males or females. The secondary analyses showed differences between urban and rural populations for all outcomes, and when comparing the most fatigued and worst QoL (75th percentile and above) to less diseased participants.
CONCLUSION: In this study, we found modest and context-dependent associations between certain urban features of the external exposome, particularly neighborhood socioeconomic status and access to blue space, and dimensions of long COVID severity. The heterogeneity of results across sex, urbanicity, and analytical methods highlights the need for targeted follow-up studies in diverse populations.
OBJECTIVES: To identify specific environmental factors most strongly associated with long COVID severity, measured as fatigue, quality of life (QoL), and number of symptoms, within a population-based sample of individuals with self-reported long COVID, and to compare results across multiple statistical approaches.
METHODS: We analyzed data from 1,108 participants in the Lifelines COVID-19 cohort who had self-reported long COVID and had complete covariate information. Outcome information was obtained through questionnaires, and environmental exposures were estimated by geocoded linkage to participant's residential addresses. Analyses were stratified by sex due to large differences in outcome distribution. Exposure-outcome associations were estimated using traditional regression models, horseshoe regression, Bayesian Model Averaging, and Random Forest, with adjustment for age, BMI, and education level. In secondary analyses we further stratified for urbanicity and severity of complaints.
RESULTS: Findings varied across analytical methods. The most consistent associations were observed in men: higher neighborhood prevalence of low-income residents was associated with greater fatigue, represented by lower scores (B=-2.09), and greater distance to blue space was associated with lower QoL, represented by higher scores (B=0.26). We did not find any associations in females, or the number of present symptoms in either males or females. The secondary analyses showed differences between urban and rural populations for all outcomes, and when comparing the most fatigued and worst QoL (75th percentile and above) to less diseased participants.
CONCLUSION: In this study, we found modest and context-dependent associations between certain urban features of the external exposome, particularly neighborhood socioeconomic status and access to blue space, and dimensions of long COVID severity. The heterogeneity of results across sex, urbanicity, and analytical methods highlights the need for targeted follow-up studies in diverse populations.