Skip Content
You are currently on the new version of our website. Access the old version .
NutrientsNutrients
  • This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
  • Article
  • Open Access

2 February 2026

Dietary Diversity, Dietary Patterns, and Cardiometabolic Health in University Students: A Cross-Sectional Study

,
,
,
,
,
,
,
and
1
Carrera de Nutrición y Dietética, Facultad de Ciencias de la Salud, Universidad Católica de Santiago de Guayaquil, Guayaquil 090615, Ecuador
2
Maestría de Nutrición y Dietética, Facultad de Ciencias de la Salud, Universidad de Las Américas (UDLA), Quito 170503, Ecuador
3
Carrera de Nutrición y Dietética, Facultad de Ciencias Médicas, Universidad de Guayaquil, Guayaquil 090615, Ecuador
4
Carrera de Fisioterapia, Facultad de Ciencias de la Salud, Universidad Católica de Santiago de Guayaquil, Guayaquil 090615, Ecuador
This article belongs to the Special Issue The Impact of the Food Environment on Diet and Health

Abstract

Background: Cardiometabolic risk is increasingly observed in young adults, particularly during university years, and is not limited to individuals with elevated body mass index. Emerging evidence highlights the presence of normal weight obesity—characterized by excess adiposity and unfavorable body composition despite normal BMI—which may confer early metabolic vulnerability. Dietary diversity is often promoted as a marker of dietary adequacy; however, its relationship with adiposity, body composition, and muscular health remains inconsistent, particularly in Latin American populations. Moreover, few studies have directly contrasted dietary diversity indicators with empirically derived dietary patterns in relation to cardiometabolic and functional outcomes. Objective: To examine the associations between dietary diversity, dietary patterns, and indicators of adiposity, muscular strength, and relative muscle mass in Ecuadorian university students. Methods: A cross-sectional study was conducted among 349 undergraduate students aged 18–26 years enrolled in health sciences programs in Ecuador. Dietary intake was assessed using a validated food frequency questionnaire. Dietary diversity was quantified using the Food and Agriculture Organization’s Individual Dietary Diversity Score, while dietary patterns were identified through principal component analysis followed by k-means clustering. Outcomes included excess body weight, relative muscle mass assessed by bioelectrical impedance analysis, and handgrip strength. Multivariable Poisson and linear regression models were fitted, adjusting for age, sex, academic program, physical activity level, and pre-existing conditions. Results: Despite their young age and low prevalence of diagnosed disease, approximately one-third of the participants exhibited markers of early cardiometabolic risk, including excess body weight and central adiposity. Higher dietary diversity was independently associated with a higher prevalence of excess body weight (adjusted prevalence ratio per one-unit increase in IDDS: 1.17; 95% CI: 1.06–1.30) and with greater relative muscle mass (adjusted β = 0.13; 95% CI: 0.05–0.22), whereas no association was observed with handgrip strength. In contrast, dietary patterns derived from multivariate analysis showed no significant associations with adiposity, muscular strength, or relative muscle mass after adjustment. Conclusions: In this young adult population, dietary diversity captured aspects of overall dietary exposure associated with both increased adiposity and greater lean mass, but not with muscular strength. Empirically derived dietary patterns demonstrated limited discriminatory capacity, likely reflecting dietary homogeneity within the cohort. These findings indicate that dietary diversity alone does not necessarily reflect diet quality and underscore the importance of interpreting diversity metrics alongside indicators of food quality, energy density, and body composition when evaluating early cardiometabolic risk in contemporary food environments.

Article Metrics

Citations

Article Access Statistics

Article metric data becomes available approximately 24 hours after publication online.