Specific Macronutrient clusters associated with lower mortality Risk: Evidence from NHANES 1999–2018

Abstract

Introduction

Accumulating evidence suggest that imbalanced macronutrient composition would increase the risk of chronic diseases. However, previous studies that predominantly focused on individual macronutrients often failed to thoroughly elucidate this complex association.

Objectives

This study aimed to comprehensively analyze the relationship between macronutrient clusters and all-cause mortality.

Methods

The study included 26,615 adults aged 20–75 years from the National Health and Nutrition Examination Survey (NHANES) 1999–2018. A three-dimensional cube method was employed to categorize clusters of macronutrients intake. The association between dietary macronutrient clusters and all-cause mortality was investigated using Cox proportional hazards modeling and restricted cubic spline (RCS) analysis.

Results

Over a weighted median follow-up duration of 7.58 years, 3,998 deaths were recorded. After adjusting for potential confounders, compared with the reference Cluster _Pm:Fm:Cmh, 4 specific Clusters were associated with reduced all-cause mortality: Cluster _Pm:Fm:Cm (HR: 0.79, 95 % CI: 0.67–0.92), Cluster _Pm:Fmh:Cml (HR: 0.76, 95 % CI: 0.61–0.95), Cluster _Pm:Fmh:Cm (HR: 0.86, 95 % CI: 0.75–0.97), and Cluster _Pl:Fm:Cmh (HR: 0.73, 95 % CI: 0.60–0.89). Three-node RCS analysis revealed non-linear relationships between carbohydrate within Cluster _Pm:Fm:Cm and protein within Cluster _Pl:Fm:Cmh and overall mortality. Subgroup and sensitivity analyses corroborated the robustness of these associations across different age, gender, and energy intake levels.

Conclusions

This study employed a three-dimensional cube approach to categorize the human macronutrients intake into 24 clusters. Cluster _Pm:Fm:Cm, Clusters _Pm:Fmh:Cml, Cluster _Pm:Fmh:Cm, and Cluster _Pl:Fm:Cmh exhibited a lower mortality risk. Different clusters of macronutrients could be a precondition in nutrition intervene strategy.