Associations between Dietary Patterns and Blood Pressure in a Clinical Sample of Overweight Adults.

Background Dietary pattern analysis provides important evidence revealing diet–disease relationships. It may be especially useful in areas less well researched, such as diet and hypertension in clinical populations. Objective The aim of this study was to identify the association between dietary patterns and blood pressure (BP) in a sample of overweight adults volunteering for a clinical trial for weight loss. Design This cross-sectional analysis used baseline data from the HealthTrack study, a 12-month randomized controlled trial. Dietary intake was evaluated with 4-day food records. Participants/setting Participants were 328 adults recruited from the Illawarra region of New South Wales, Australia, between May 2014 and April 2015. Main outcome measures Resting BP and 24-hour urine sodium and potassium were measured. Statistical analysis Dietary patterns were derived by principal component analysis from 21 food groups. Multiple regression analysis was performed to assess the association between the extracted dietary patterns and BP. Results The participants’ mean age was 43.6±8.0 years, mean body mass index was 32.4±4.2, and mean systolic BP/diastolic BP was 124.9±14.5/73.3±9.9 mm Hg. Six major dietary patterns were identified: “nuts, seeds, fruit, and fish,” “milk and meat,” “breads, cereals, and snacks,” “cereal-based products, fats, and oils,” “alcohol, eggs, and legumes,” and “savoury sauces, condiments, and meat.” The “nuts, seeds, fruit, and fish” dietary pattern was significantly and inversely associated with systolic BP ( F [7,320]=15.248; P <0.0005; adjusted R 2 =0.234 and diastolic BP ( F [7,320]=17.351; P <0.0005; adjusted R 2 =0.259) and sodium-to-potassium ratio ( F [7,320]=6.210; P <0.0005; adjusted R 2 =0.100). Conclusions A dietary pattern rich in nuts, seeds, fruit, and fish was inversely associated with blood pressure in this clinical sample. The findings suggest that current dietary guidelines are relevant to an overweight clinical population and support the value of dietary pattern analysis when exploring the diet–disease relationship. [ABSTRACT FROM AUTHOR]