Quantifying Diet Intake and Its Association with Cardiometabolic Risk in the UK Airwave Health Monitoring Study: A Data-Driven Approach

Associations of Systematic Inflammatory Markers with Diet Quality, Blood Pressure, and Obesity in the AIRWAVE Health Monitoring Study

Introduction

Chronic low-grade inflammation is a characteristic feature of obesity, and elevated levels of inflammation are associated with pathophysiologic consequences and a constellation of metabolic disturbances, such as hypertension. The relationships of inflammation with diet, obesity, and hypertension are complex, hence, this study aimed to assess cross-sectional relationships between inflammatory scores, diet quality, obesity, high blood pressure (BP), and hypertension in the Airwave Health Monitoring Study cohort, a large cohort of police officers and police staff in the United Kingdom.

Methods

Data from 5198 men and 3347 women who completed health screening measurements and dietary assessment between 2007 and 2012 were included (n=8545 adults). Platelet-to-lymphocyte ratio (PLR), neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), and the systemic immune-inflammation index (SII) were calculated. Diet quality was evaluated using the Nutrient-Rich Food 9.3 (NRF9.3) index score.

Results

Results show that a 1SD higher diet quality score, waist circumference, and systolic/diastolic BP were significantly associated with SII differences of -33.3 (95% confidence interval (CI): -49.0, -17.6), 8.2 (95% CI: 0.2, 16.6), 17.9 (95% CI: 10.1, 25.8), and 18.3 (95% CI: 10.8, 25.7) (Model 2; P<0.0001), respectively. A 1SD higher diet quality score, waist circumference, and BMI were also significantly associated with PLR (P<0.0001). The odds of elevated PLR were higher in those with higher systolic and diastolic BP (P<0.0001, P=0.0006, respectively).

Conclusion

In conclusion, the findings of this analysis add to the existing knowledge indicating a link between inflammation and conditions such as obesity, hypertension, and behavioral factors including diet quality. Of the various inflammatory scores evaluated, SII and PLR were consistently significantly associated with diet quality and these conditions.

Higher Dietary Polyphenol Intake Is Associated With Lower Blood Inflammatory Markers

BACKGROUND

Evidence suggests a link between polyphenol intake and reduced incidence of several chronic diseases. This could arise through associations between polyphenol intake and reduced systemic oxidative stress and subsequent inflammation. However, confirming this association is difficult, as few large cohorts allow for comprehensive assessments of both polyphenol intake and markers of systemic inflammation.

OBJECTIVES

To address this, polyphenol intake was assessed in the UK-based Airwave cohort using 7-d diet diaries and data from Phenol-Explorer to test for associations between polyphenol intake and blood biomarkers of inflammation.

METHODS

Participants included 9008 males and females aged 17-74 y (median age: 42 y) whose data was included in a cross-sectional analysis. Phenol-Explorer was used to estimate individuals' polyphenol intake from diet data describing the consumption of 4104 unique food items. C-reactive protein (CRP) and fibrinogen were used as blood biomarkers of inflammation.

RESULTS

There were 448 polyphenols found in reported diet items. Median total polyphenol intake was 1536 mg/d (1058-2092 mg/d). Phenolic acids and flavonoids were the main types of polyphenols, and nonalcoholic beverages, vegetables, and fruit were the primary sources. Variation in energy-adjusted polyphenol intake was explained by age, sex, salary, body mass index, education level, smoking, and alcohol consumption. Linear regressions showed inverse associations between total daily intake and both CRP (β: -0.00702; P < 0.001) and fibrinogen (β: -0.00221; P = 0.038). Associations with specific polyphenol compound groups were also found. Logistic regressions using total polyphenol intake quartiles showed stepwise reductions in the odds of elevated CRP with higher intake (6%, 23%, and 24% compared with quartile 1; P = 0.003), alongside 3% and 7% lower odds per unit of polyphenol consumption equivalent to 1 cup of tea or coffee per day.

CONCLUSIONS

This study describes polyphenol intake in a large, contemporary UK cohort. We observed associations between higher intake and lower CRP and fibrinogen. This contributes to evidence supporting the health benefits of dietary polyphenols.

Effect of the Association of Fixed Oils from Abelmoschus esculentus (L.) Moench, Euterpe oleracea Martius, Bixa orellana Linné and Chronic SM® on Atherogenic Dyslipidemia in Wistar Rats

Dyslipidemia presents high levels of serum cholesterol and is characterized as a risk factor for cardiovascular diseases, especially for the development of atherosclerosis. E. oleracea oil (OFEO), A. esculentus oil (OFAE), B. orellana oil (OFBO), and Chronic SM® granules (CHR) are rich in bioactive compounds with the potential to treat changes in lipid metabolism. This study investigated the effects of treatments with oils from A. esculentus, E. oleracea, B. orellana, and Chronic SM® on Cocos nucifera L. saturated-fat-induced dyslipidemia. The chromatographic profile showed the majority presence of unsaturated fatty acids in the tested oils. The quantification of tocotrienols and geranylgeraniol in OFBO and CHR was obtained. Treatments with OFEO, OFAE, OFBO, and CHR were able to significantly reduce glycemia, as well as hypertriglyceridemia, total cholesterol, and LDL-cholesterol, besides increasing HDL-cholesterol. The treatments inhibited the formation of atheromatous plaques in the vascular endothelium of the treated rats. The obtained results suggest that the OFEO, OFAE, OFBO, and CHR exhibit antidyslipidemic effects and antiatherogenic activity.

Improving Heart Disease Risk Through Quality-Focused Diet Logging: Pre-Post Study of a Diet Quality Tracking App

Background

Diet-tracking mobile apps have gained increased interest from both academic and clinical fields. However, quantity-focused diet tracking (eg, calorie counting) can be time-consuming and tedious, leading to unsustained adoption. Diet quality—focusing on high-quality dietary patterns rather than quantifying diet into calories—has shown effectiveness in improving heart disease risk. The Healthy Heart Score (HHS) predicts 20-year cardiovascular risks based on the consumption of foods from quality-focused food categories, rather than detailed serving sizes. No studies have examined how mobile health (mHealth) apps focusing on diet quality can bring promising results in health outcomes and ease of adoption.

Objective

This study aims to design a mobile app to support the HHS-informed quality-focused dietary approach by enabling users to log simplified diet quality and view its real-time impact on future heart disease risks. Users were asked to log food categories that are the main predictors of the HHS. We measured the app’s feasibility and efficacy in improving individuals’ clinical and behavioral factors that affect future heart disease risks and app use.

Methods

We recruited 38 participants who were overweight or obese with high heart disease risk and who used the app for 5 weeks and measured weight, blood sugar, blood pressure, HHS, and diet score (DS)—the measurement for diet quality—at baseline and week 5 of the intervention.

Results

Most participants (30/38, 79%) used the app every week and showed significant improvements in DS (baseline: mean 1.31, SD 1.14; week 5: mean 2.36, SD 2.48; 2-tailed t test t₂₉=−2.85; P=.008) and HHS (baseline: mean 22.94, SD 18.86; week 4: mean 22.15, SD 18.58; t₂₉=2.41; P=.02) at week 5, although only 10 participants (10/38, 26%) checked their HHS risk scores more than once. Other outcomes, including weight, blood sugar, and blood pressure, did not show significant changes.

Conclusions

Our study showed that our logging tool significantly improved dietary choices. Participants were not interested in seeing the HHS and perceived logging diet categories irrelevant to improving the HHS as important. We discuss the complexities of addressing health risks and quantity- versus quality-based health monitoring and incorporating secondary behavior change goals that matter to users when designing mHealth apps.

Circadian, Sleep and Caloric Intake Phenotyping in Type 2 Diabetes Patients With Rare Melatonin Receptor 2 Mutations and Controls: A Pilot Study

Background

Melatonin modulates circadian rhythms in physiology and sleep initiation. Genetic variants of the MTNR1B locus, encoding the melatonin MT₂ receptor, have been associated with increased type 2 diabetes (T2D) risk. Carriers of the common intronic MTNR1B rs10830963 T2D risk variant have modified sleep and circadian traits such as changes of the melatonin profile. However, it is currently unknown whether rare variants in the MT₂ coding region are also associated with altered sleep and circadian phenotypes, including meal timing.

Materials and Methods

In this pilot study, 28 individuals [50% male; 46–82 years old; 50% with rare MT₂ mutations (T2D MT₂)] wore actigraphy devices and filled out daily food logs for 4 weeks. We computed circadian, sleep, and caloric intake phenotypes, including sleep duration, timing, and regularity [assessed by the Sleep Regularity Index (SRI)]; composite phase deviations (CPD) as well a sleep timing-based proxy for circadian misalignment; and caloric intake patterns throughout the day. Using regression analyses, we estimated age- and sex-adjusted mean differences (MD) and 95% confidence intervals (95%CI) between the two patient groups. Secondary analyses also compare T2D MT₂ to 15 healthy controls.

Results

Patients with rare MT₂ mutations had a later sleep onset (MD = 1.23, 95%CI = 0.42;2.04), and midsleep time (MD = 0.91, 95%CI = 0.12;1.70), slept more irregularly (MD in SRI = −8.98, 95%CI = −16.36;−1.60), had higher levels of behavioral circadian misalignment (MD in CPD = 1.21, 95%CI = 0.51;1.92), were more variable in regard to duration between first caloric intake and average sleep offset (MD = 1.08, 95%CI = 0.07;2.08), and had more caloric episodes in a 24 h day (MD = 1.08, 95%CI = 0.26;1.90), in comparison to T2D controls. Secondary analyses showed similar patterns between T2D MT₂ and non-diabetic controls.

Conclusion

This pilot study suggests that compared to diabetic controls, T2D MT₂ patients display a number of adverse sleep, circadian, and caloric intake phenotypes, including more irregular behavioral timing. A prospective study is needed to determine the role of these behavioral phenotypes in T2D onset and severity, especially in view of rare MT₂ mutations.