Superficial Fungal Infection Associations with Comorbid Diseases and Risk Factors: An Analysis of Global Burden of...

Superficial fungal infections caused by dermatophyte and non-dermatophyte species are increasing globally. While several comorbid diseases and risk factors have been associated with fungal infections at the individual level, their epidemiological relationships at the population level remains poorly characterized.

We aimed to examine population-level associations between the burden of superficial fungal infections and selected comorbid conditions and risk factors, stratified by age, sex and country.

We obtained years lived with disability (YLDs) for superficial fungal infections, diabetes, psoriasis, and atopic dermatitis and summary exposure values (SEVs) for high body mass index (BMI) and high alcohol intake from Global Burden of Disease Study 2023. Data were obtained for Australia, Brazil, the United Kingdom and the United States for males and females younger than 20 years, 20 to 54 years and 55+ years old. Pearson correlation coefficients were calculated between fungal infection YLDs and each comorbid condition (YLDs) and risk factor (SEVs).

Significant positive correlations were observed between superficial fungal infection burden and diabetes (R = 0.6-0.98), high BMI (R = 0.75-0.95), psoriasis (R = 0.59-0.96), and atopic dermatitis (R = 0.51-0.93) in older adults (55 years+). Correlations with high alcohol consumption were more variable across regions and sex. In young-middle-aged adults (20-54 years), moderate-to-strong correlations (R ~ 0.8-0.9) were observed, although patterns were less consistent across countries. In individuals < 20 years, associations were generally weaker, with some positive correlations observed for atopic dermatitis (R = 0.4-0.7) in select countries.

The findings demonstrate population-level associations between superficial fungal infections and metabolic, inflammatory, and behavioural risk factors, with stronger correlations observed in older age groups. These patterns may reflect shared demographic, epidemiologic, and clinical patterns across conditions.