METABOLIC MULTIMORBIDITY BURDEN survey suggests that cardiovascular, kidney, and metabolic (CKM) disease burden may explain important differences in health status beyond body mass index (BMI).
Researchers analysed pooled 2017 and 2019 Behavioural Risk Factor Surveillance System data from 677,784 US adults to develop a Metabolic Multimorbidity Burden Index (MMBI)
Metabolic Multimorbidity Burden Index Development
The MMBI is a self-report tool designed to quantify CKM-related multimorbidity when laboratory biomarkers are unavailable.
The index incorporated five self-reported conditions: diabetes, hypertension, hypercholesterolaemia, chronic kidney disease, and cardiovascular disease.
The study aimed to determine whether combining the MMBI with BMI could better characterise self-rated health and health related quality of life outcomes.
Higher MMBI scores were consistently associated with poorer self-rated health.
In the fully adjusted model, each one standard deviation increase in MMBI was linked to significantly greater odds of poor self-rated health.
Obesity and Joint Risk Patterns
When BMI categories were cross classified with MMBI tertiles, substantial heterogeneity emerged.
Compared with adults of normal weight and low MMBI, those of normal weight and high MMBI had markedly increased odds of poor self-rated health. This exceeded the estimate observed among adults with obesity and low MMBI.
The highest risk was observed among adults with obesity and high MMBI.
Statistical interaction between BMI and MMBI was also identified, indicating that metabolic burden and body fat mass jointly contributed to health risk.
Implications for Population Health Surveillance
The findings suggest that Metabolic Multimorbidity Burden may capture meaningful health differences that BMI alone does not identify.
Similar patterns were observed for frequent physical distress and frequent mental distress, supporting the broader relevance of the index to health-related quality of life outcomes.
The researchers emphasised that the MMBI is intended as a population surveillance tool rather than a clinical prediction instrument.
Nevertheless, the results indicate that integrating Metabolic Multimorbidity Burden with BMI may provide a more informative framework for identifying health-related risk heterogeneity in settings where biomarker data are unavailable.
Future research will be needed to evaluate its performance in other populations and against clinical outcomes.
Reference
Zhang X et al. Joint burden of obesity and CKM-related metabolic multimorbidity in US adults: development of a survey-based MMBI. Sci Rep. 2026;DOI:10.1038/s41598-026-57886-4
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