Frontiers in public health · 2026
Beyond radiation dosimetry: metabolic burden and a possible healthy worker survivor pattern in the medical imaging workforce.
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Yan Saike, Wu Jianhui, Liu Yuanping, Si Wen, Yan Shengguang
Аннотация
OBJECTIVE: Current occupational health protocols in radiology remain strongly focused on ionizing radiation while underemphasizing metabolic health concerns potentially associated with sedentary and shift-based occupational environments. This study examined the prevalence of Non-Alcoholic Fatty Liver Disease (NAFLD) in medical imaging professionals and evaluated whether the observed tenure-related pattern was more consistent with early-career occupational burden and possible survivor-selection processes than with a simple linear cumulative-risk model.
METHODS: A cross-sectional analysis was conducted among 235 medical imaging professionals. NAFLD was diagnosed by abdominal ultrasonography according to APASL-based criteria. Restricted Cubic Spline (RCS) regression and multivariable logistic models were used to evaluate tenure-related patterns and metabolic predictors. Supplementary analyses further assessed waist circumference, work-schedule characteristics, multicollinearity using variance inflation factors (VIFs), and model robustness across alternative specifications.
RESULTS: The cohort exhibited a NAFLD prevalence of 47.7%. Occupational tenure showed a non-linear pattern, with prevalence rates of 44.1%, 61.9%, 32.5%, and 52.3% across the <5 years, 5-10 years, 10-20 years, and >20 years groups, respectively. Participants with NAFLD had a larger waist circumference than those without NAFLD (112.7 ± 5.1 cm vs. 105.6 ± 6.5 cm). Across sensitivity analyses, BMI remained the most stable metabolic predictor (OR 1.45-1.49), whereas the tenure-related effect was less stable. These findings are compatible with a possible survivor-selection pattern but require cautious interpretation.
CONCLUSION: These findings do not support a simple linear interpretation of tenure-related metabolic risk. Instead, they suggest that adiposity-related metabolic burden is more robustly associated with NAFLD than occupational tenure alone, and that the observed tenure pattern may be compatible with survivor-selection processes. Future studies should directly quantify shift-related, circadian, and behavioral exposures, and metabolic surveillance may usefully complement existing dosimetry-centered occupational monitoring.
METHODS: A cross-sectional analysis was conducted among 235 medical imaging professionals. NAFLD was diagnosed by abdominal ultrasonography according to APASL-based criteria. Restricted Cubic Spline (RCS) regression and multivariable logistic models were used to evaluate tenure-related patterns and metabolic predictors. Supplementary analyses further assessed waist circumference, work-schedule characteristics, multicollinearity using variance inflation factors (VIFs), and model robustness across alternative specifications.
RESULTS: The cohort exhibited a NAFLD prevalence of 47.7%. Occupational tenure showed a non-linear pattern, with prevalence rates of 44.1%, 61.9%, 32.5%, and 52.3% across the <5 years, 5-10 years, 10-20 years, and >20 years groups, respectively. Participants with NAFLD had a larger waist circumference than those without NAFLD (112.7 ± 5.1 cm vs. 105.6 ± 6.5 cm). Across sensitivity analyses, BMI remained the most stable metabolic predictor (OR 1.45-1.49), whereas the tenure-related effect was less stable. These findings are compatible with a possible survivor-selection pattern but require cautious interpretation.
CONCLUSION: These findings do not support a simple linear interpretation of tenure-related metabolic risk. Instead, they suggest that adiposity-related metabolic burden is more robustly associated with NAFLD than occupational tenure alone, and that the observed tenure pattern may be compatible with survivor-selection processes. Future studies should directly quantify shift-related, circadian, and behavioral exposures, and metabolic surveillance may usefully complement existing dosimetry-centered occupational monitoring.