Ultra-Processed Food-Rich Dietary Proxies, Dietary-Pattern Context, and Cardiometabolic Outcomes in Spain: Weighted Evidence Consistent with Age Confounding and Possible Reverse-Causality Bias from the 2023 Spanish Health Survey.
N, C.C., JJ, Z.L., D, C.A., DM, M., A, B.P., M, C.R., A, L.d.A., R, J.G., E, R.G., & L, F.A. (2026). Ultra-Processed Food-Rich Dietary Proxies, Dietary-Pattern Context, and Cardiometabolic Outcomes in Spain: Weighted Evidence Consistent with Age Confounding and Possible Reverse-Causality Bias from the 2023 Spanish Health Survey.. Nutrients. https://doi.org/10.3390/nu18162615
N CC, JJ ZL, D CA, DM M, A BP, M CR, et al. Ultra-Processed Food-Rich Dietary Proxies, Dietary-Pattern Context, and Cardiometabolic Outcomes in Spain: Weighted Evidence Consistent with Age Confounding and Possible Reverse-Causality Bias from the 2023 Spanish Health Survey.. Nutrients. 2026; doi: 10.3390/nu18162615
N CC, JJ ZL, D CA, et al. Ultra-Processed Food-Rich Dietary Proxies, Dietary-Pattern Context, and Cardiometabolic Outcomes in Spain: Weighted Evidence Consistent with Age Confounding and Possible Reverse-Causality Bias from the 2023 Spanish Health Survey.[J]. Nutrients. 2026. DOI: 10.3390/nu18162615.
@article{n2026,
author = {Cuadrado-Corrales N and Zamorano-León JJ and Carabantes-Alarcón D and Mérida DM and Bodas-Pinedo A and Chico-Rodríguez M and Lopez-de-Andres A and Jiménez-Garcia R and Redondo-González E and Fuentes-Arroyo L},
title = {Ultra-Processed Food-Rich Dietary Proxies, Dietary-Pattern Context, and Cardiometabolic Outcomes in Spain: Weighted Evidence Consistent with Age Confounding and Possible Reverse-Causality Bias from the 2023 Spanish Health Survey.},
journal = {Nutrients},
year = {2026},
doi = {10.3390/nu18162615},
note = {PMID: 42654195},
}
TY - JOUR AU - Cuadrado-Corrales N AU - Zamorano-León JJ AU - Carabantes-Alarcón D AU - Mérida DM AU - Bodas-Pinedo A AU - Chico-Rodríguez M AU - Lopez-de-Andres A AU - Jiménez-Garcia R AU - Redondo-González E AU - Fuentes-Arroyo L TI - Ultra-Processed Food-Rich Dietary Proxies, Dietary-Pattern Context, and Cardiometabolic Outcomes in Spain: Weighted Evidence Consistent with Age Confounding and Possible Reverse-Causality Bias from the 2023 Spanish Health Survey. T2 - Nutrients PY - 2026 DO - 10.3390/nu18162615 AN - PMID:42654195 ER -
BACKGROUND/OBJECTIVES: Ultra-processed foods (UPFs) are linked to cardiometabolic disease, but cross-sectional surveys often underestimate or invert these associations due to age structure, diagnosis-related dietary changes, and reporting bias. This study explores the potential influence of these biases and examines cross-sectional associations between dietary proxies and prevalent cardiometabolic conditions using the most recent national data from Spain. METHODS: We analyzed the 2023 Spanish Health Survey (n = 21,032). Body Mass Index (BMI) was derived from self-reported weight and height. Hypertension and diabetes were defined as self-reported medical diagnoses. Dietary items were mapped as UPF-rich proxies, processed-meat exposure, protective dietary markers, and beverage comparators. Weighted logistic models were adjusted for sociodemographic and lifestyle factors. Bias-probing analyses included stratification by self-rated health, exclusion of severe chronic comorbidities (n = 4107), and model-based beverage contrasts. RESULTS: Prevalence reached 53.6% for excess weight, 23.9% for prevalent hypertension, and 7.4% for prevalent diabetes. Weekly fast-food consumption was consistently associated with excess weight (OR 1.20, 95% CI 1.07-1.35), obesity (OR 1.28, 95% CI 1.09-1.50), prevalent hypertension (OR 1.18, 95% CI 1.02-1.37), and prevalent diabetes (OR 1.33, 95% CI 1.10-1.61). Excluding participants with severe chronic comorbidities strengthened the fast-food association with prevalent diabetes (OR 1.46, 95% CI 1.17-1.81). CONCLUSIONS: Fast food emerged as the most consistent adverse dietary marker co-occurring across all prevalent outcomes, whereas processed meat was specifically associated with prevalent excess weight and obesity rather than prevalent cardiometabolic diagnoses. Stratified and sensitivity analyses provided empirical patterns consistent with age confounding and possible post-diagnosis dietary changes influencing cross-sectional associations, highlighting the need for cautious interpretation in public health surveillance.