ArticleFrontiers in public health2024
Association between the cardiometabolic index and osteoporosis: a cross-sectional study of the NHANES.
Article in Frontiers in public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- The association between cardiometabolic index and hypertension-diabetes comorbidity among adults aged 45 and older: evidence from two national databases.BMC endocrine disorders · 2026Article
- Higher cardiometabolic index elevates the risk of hyperuricemia in the elderly: findings from the China health and retirement longitudinal study.Annals of medicine · 2025Article
- Association of the cardiometabolic index with sarcopenia among U.S. adults: NHANES 2011-2018 findings.PloS one · 2025Article
- Association between cardiometabolic index and stroke risk: insights from the CHARLS cohort study.Frontiers in neurology · 2025Article
- Assessment of the Association Between Cardiac Metabolic Markers and Carotid Atherosclerosis, and the Role of Insulin Resistance.Diabetes, metabolic syndrome and obesity : targets and therapy · 2025Article
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Authors and funding
5 authors.
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Abstract
Background: The cardiometabolic index (CMI) is a novel metabolic biomarker, but research on its association with osteporosis (OP) is limited. The objective of this research was to clarify the relationship between CMI and OP in the older adult population of the United States. Methods: This study conducted a cross-sectional analysis using NHANES data 2007-2018 with exclusion of 2011-2012 and 2015-2016 cycles. Logistic regression was used to investigate the relationship between CMI and OP prevalence. Restricted cubic spline curve (RCS) and threshold saturation analyses were performed to explore the nonlinear association between CMI and OP prevalence. Subgroup analyses, sensitivity analyses, and additional analyses were conducted to ensure the robustness and reliability of the findings. Results: The study included 4,191 participants, revealing that those with OP had significantly lower CMI levels. Logistic regression revealed a strong inverse correlation between Log CMI and OP (OR = 0.72, 95% CI = 0.59-0.88), which persisted after adjusting for covariates. RCS analysis revealed a nonlinear inverse relationship with the critical threshold at CMI = 0.93. Below this threshold, each unit increase in CMI was associated with a 37% reduction in OP prevalence, but changes above this threshold were not significant. Subgroup and sensitivity analyses confirmed the robustness of the findings. Conclusion: Elevated CMI exhibited a robust inverse correlation with the prevalence of OP in the older adult U.S. population. Maintaining a moderate CMI significantly diminishes the risk of developing OP.
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