Metal Mixture Inflammatory Index and diabetes risk in US adults: a cross-sectional analysis of NHANES 1999–2020 and development of a least absolute shrinkage and selection operator (LASSO)-based prediction model
Authors' conclusion
MMII is independently and linearly associated with diabetes risk. Metal exposures may enhance future risk stratification for diabetes. Prospective studies are warranted to confirm causal mechanisms.
Study context
- Population
- US adults, NHANES 1999–2020
- Participants
- 23,288 adults
- Exposure
- Higher vs lower Metal Mixture Inflammatory Index
- Outcome
- Prevalent diabetes
Methodological detailssurvey-weighted logistic regression, restricted cubic splines, LASSO-based prediction model (nomogram)
- Survey-weighted logistic regression
- Restricted cubic splines
- LASSO-based prediction model (nomogram)
Main finding
As reported in the abstract
Diabetes
Odds ratio (95% CI)P value
Per 0.1-unit increase in MMIImultivariable adjusted
1.02(1.00–1.04)
P = 0.02Q4vs Q1
1.26(1.04–1.52)
P = 0.016Observational data: associations, not effects.
Further findings
Subgroup analyses
- Stronger associations among men, non-Hispanic white participants, former smokers, current alcohol users and individuals without hypertension
LASSO-based nomogram performance
- AUC
- 0.869 (95% CI 0.863 to 0.875)
- Good calibration and net clinical benefit
Original publication
Metal Mixture Inflammatory Index and diabetes risk in US adults: a cross-sectional analysis of NHANES 1999–2020 and development of a LASSO-based prediction model. BMJ Open Diabetes Res Care. Published 29 December 2025. doi:10.
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