Higher ultra processed foods intake is associated with low muscle mass in young to middle-aged adults: a cross-sectional NHANES study

Abstract

DesignUltra-processed foods (UPFs) have become a pressing global health concern, prompting investigations into their potential association with low muscle mass in adults.MethodsThis cross-sectional study analyzed data from 10,255 adults aged 20−59 years who participated in the National Health and Nutritional Examination Survey (NHANES) during cycles spanning from 2011 to 2018. The primary outcome, low muscle mass, was assessed using the Foundation for the National Institutes of Health (FNIH) definition, employing restricted cubic splines and weighted multivariate regression for analysis. Sensitivity analysis incorporated three other prevalent definitions to explore optimal cut points for muscle quality in the context of sarcopenia.ResultsThe weighted prevalence of low muscle mass was 7.65%. Comparing the percentage of UPFs calories intake between individuals with normal and low muscle mass, the values were found to be similar (55.70 vs. 54.62%). Significantly linear associations were observed between UPFs consumption and low muscle mass (P for non-linear = 0.7915, P for total = 0.0117). Upon full adjustment for potential confounding factors, participants with the highest UPFs intake exhibited a 60% increased risk of low muscle mass (OR = 1.60, 95% CI: 1.13 to 2.26, P for trend = 0.003) and a decrease in ALM/BMI (β = −0.0176, 95% CI: −0.0274 to −0.0077, P for trend = 0.003). Sensitivity analysis confirmed the consistency of these associations, except for the International Working Group on Sarcopenia (IWGS) definition, where the observed association between the highest quartiles of UPFs (%Kcal) and low muscle mass did not attain statistical significance (OR = 1.35, 95% CI: 0.97 to 1.87, P for trend = 0.082).ConclusionOur study underscores a significant linear association between higher UPFs consumption and an elevated risk of low muscle mass in adults. These findings emphasize the potential adverse impact of UPFs on muscle health and emphasize the need to address UPFs consumption as a modifiable risk factor in the context of sarcopenia.

Ultra-Processed Foods: A Narrative Review of the Impact on the Human Gut Microbiome and Variations in Classification Methods

“…However, observational studies have the advantage of a generally larger sample size, longer time periods that data are collected, and can capture many different types of non-communicable diseases in a single study. For example, several studies in Table 3 utilize data from large cohort studies such as the European Prospective Investigation into Cancer and Nutrition (EPIC) and NHANES, which allows for analysis of thousands of individuals over many years [ 76 , 77 , 78 , 79 , 80 ].…”

“…Of the studies in Table 3 , eight used FFQs [ 81 , 82 , 83 , 84 , 85 , 86 , 87 , 88 ], seven used 24 h dietary recalls [ 77 , 79 , 80 , 89 , 90 , 91 , 92 ], and two used a combination of methods (FFQs and food records) [ 76 , 78 ] to collect food information. Each of these methods have been validated for use in dietary research, but limitations exist that make food processing classification difficult in some cases.…”

“…Each of these methods have been validated for use in dietary research, but limitations exist that make food processing classification difficult in some cases. When there was ambiguity in the classification of foods, studies resolved these items by several methods: group discussion and consensus [ 83 , 86 , 90 , 91 , 92 ], discussion and defaulting to a lower level of processing [ 77 , 81 , 82 , 85 , 86 , 88 , 89 ], expanding discussion to an external group [ 87 ], and utilizing external resources such as grocery store labels [ 84 , 87 , 90 , 91 ]. As shown, some studies used a combination of these methods, while others did not describe how they worked to resolve discrepancies.…”

“…Kong, 2024 [77] Two 24 h dietary recalls FNDDS and NNDSR NHANES food codes were obtained which categorized foods according to NOVA. Homemade dishes with unknown ingredients were classified according to their expected components.…”