ArticleJournal of epidemiology and global health2024
Variation of All-Cause Mortality with Fat-Free Mass Index (FFMI) and Fat Mass Index (FMI) in Individuals with Asthma: Results from the NHANES Database Retrospective Cohort Study.
Article in Journal of epidemiology and global health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Tramadol use is associated with reduced 28-day mortality in ICU patients after cardiac surgery: a retrospective study based on the MIMIC-IV database.Frontiers in pharmacology · 2026Article
- Development and Validation of a Machine Learning‑Based Predictive Model for Assessing the Risk of Comorbid Depression in Patients With Asthma.Alpha psychiatry · 2025Article
- Factors Associated with Changes in Skeletal Muscle Mass in Medical Health Checkups.Journal of clinical medicine · 2025Article
- Association of dietary intake of folate, serum folate, and red blood cell folate with mortality risk in patients with depression: a population-based longitudinal cohort study.Journal of health, population, and nutrition · 2025Article
- Exploring the relationship between fat mass index and metabolic syndrome among cancer patients in the U.S: An NHANES analysis.Scientific reports · 2025Article
- Physical Activity and Sedentary Time Correlate with Body Composition in Patients with Asthma; a Multicenter Observational Study.Journal of asthma and allergy · 2025Article
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Abstract
backgroundThe relationship between fat-free mass index (FFMI), fat mass index (FMI), and mortality in patients with asthma remains unknown. This study aimed to examine the associations between FFMI and FMI and all-cause mortality in a cohort of American adults diagnosed with asthma.
methodsThis study included 15,200 adults from NHANES. To assess mortality, we linked participant records to the National Death Index. FMI and FFMI were measured and evaluated using dual-energy X-ray absorptiometry (DXA). Survival differences across quintiles of FFMI and FMI were explored using Kaplan-Meier plots and log-rank tests, with the proportional hazards assumption assessed using Schoenfeld residuals. Cox proportional hazards regression models were used to estimate the hazard ratios (HRs) for mortality associated with FFMI and FMI, adjusting for potential confounders including age, sex, smoking status, physical activity, and other relevant factors. Additionally, stratified analyses based on theoretical considerations were conducted to identify subgroups of individuals exhibiting an elevated risk of mortality. This study also examined the nonlinear relationships between FFMI, FMI, and mortality using restricted cubic splines (RCS).
resultsAfter a median follow-up of 184 months, 12.11% of individuals had died. Kaplan-Meier plots revealed significant differences in all-cause mortality among patients with asthma across the FFMI and FMI quintiles. Specifically, individuals in the lowest FFMI quintile (Q1, 10.4-16.0, representing the range of FFMI values) exhibited a significantly increased risk of all-cause mortality (HR: 4.63; 95% CI: 1.59, 13.5; p < 0.01). Similarly, elevated risks of all-cause mortality were observed in the upper three quintiles of FMI, with Q3 (4.8-6.1) having an HR of 2.9 (95% CI: 1.20, 7.00; p < 0.05), Q4 (6.2-8.3) having an HR of 3.37 (95% CI: 1.41, 8.03; p < 0.01), and Q5 (8.4-22.8) having an HR of 4.6 (95% CI: 1.31, 16.2; p < 0.05). Moreover, the risk of all-cause mortality increased with increasing FMI and decreasing FFMI (p for non-linearity < 0.001 in both cases). Subgroup analyses further elucidated these associations across different categories. In examining the association between FMI and all-cause mortality among asthma patients across various subgroups, a heightened mortality risk found among males, individuals with medium education levels, medium income levels, and those who consume alcohol.
conclusionsThe study shows that both high FMI and low FFMI are associated with increased mortality in patients with asthma. These findings underscore the critical role of FMI and FFMI in the health management of asthma patients. Therefore, it is recommended that clinicians proactively monitor and adjust these indices to improve patient prognosis and enhance health outcomes for individuals with asthma..
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