Dietary Fats Substitution and Blood Pressure Levels: A Longitudinal Study in Mexican Adults

Authors:
Open Access
Publisher website
Google Scholar
Abstract
Background: Dietary patterns impact blood pressure (BP) levels, but the potential impact of replacing specific types of fats with proteins or carbohydrates, in isocaloric models, on BP remains unclear. Objective: This study evaluates the longitudinal association between the substitution of different types of fats with proteins or carbohydrates and changes in BP in a Mexican population. Methods: We analyzed data from 1448 adults (mean age at baseline: 45 years; 73.3% women) from the Health Workers Cohort Study, followed over 13 years. Trained personnel measured systolic (SBP) and diastolic (DBP) blood pressure following standard procedures and techniques at baseline and follow-up. Macronutrient intake was assessed with a validated semi-quantitative food frequency questionnaire. Generalized Estimating Equations (GEE) for hypertension and fixed-effects linear regression for BP were conducted using isocaloric substitution models. Each estimate reflects the effect of a 3% energy substitution of specific fats for carbohydrates or proteins. Results: Substituting 3% of energy intake of polyunsaturated fat (PUFA) in place of vegetable protein (β = −2.94, 95% CI: −5.02, −0.86), animal protein (β = −2.68, 95% CI: −4.73, −0.63), low glycemic index (LGI) carbohydrates (β = −2.63, 95% CI: −4.40, −0.86), and high glycemic index (HGI) carbohydrates (β = −2.52, 95% CI: −4.31, −0.74) was associated with a significant reduction in SBP. Substituting 3% of the energy intake of PUFA in place of different types of carbohydrates was associated with lower odds of hypertension. PUFA was not associated with changes in DBP. Conclusions: Our findings suggest that exchanging PUFA for carbohydrates or proteins is associated with reduced SBP and a lower risk of hypertension, highlighting the importance of macronutrient composition independent of total energy intake and other fat types, which may have a substantial impact at the population level.
Funding Information
  • Consejo Nacional de Ciencia y Tecnologia (7876, 87783, 262233, 26267M, SALUD-2010-01-139796, SALUD-2011-01-161930, CB-2013-01-221628, CF-2019-102962)

This publication has 56 references indexed in Scilit: