Description of the updated nutrition calculation of the Oxford WebQ questionnaire and comparison with the previous version among 207,144 participants in UK Biobank

Evaluation of the New Individual Fatty Acid Dataset for UK Biobank: Analysis of Intakes and Sources in 207,997 Participants

The Oxford WebQ is an online 24 h dietary assessment tool used by several large prospective studies. This study describes the creation of the new individual fatty acid (FA) dataset for the Oxford WebQ and reports intakes and sources of dietary individual FAs in the UK Biobank. Participants who completed ≥1 (maximum of five) 24 h dietary assessments were included (n = 207,997). Nutrient intakes were obtained from the average of all completed 24 h dietary assessments. Nutrient data from the UK McCance and Widdowson's The Composition of Foods and the US Department of Agriculture food composition tables were used to calculate intakes of 21 individual FAs. The individual FA dataset included 10 saturated fatty acids (SFAs), 4 monounsaturated fatty acids (MUFAs), and 7 polyunsaturated fatty acids (PUFAs; including alpha-linolenic (18:3), eicosapentaenoic (20:5), and docosahexaenoic (22:6) acids). Palmitic (16:0; mean ± standard deviation (SD): 13.5 ± 5.7 g/d) and stearic (18:0; 5.2 ± 2.5) acids were the main contributors to SFAs, and the main sources of these were cereals and cereal products (mostly desserts/cakes/pastries), milk and milk products (mostly cheese and milk), and meat and meat products. Oleic acid (18:1; 24.2 ± 9.8) was the main MUFA, derived mainly from cereals and cereal products, and meat and meat products. Linoleic acid (18:2; 9.7 ± 4.3) was the main PUFA, derived mostly from cereals and cereal products, and vegetables (including potatoes) and vegetable dishes. The individual FA dataset for the Oxford WebQ will allow future investigations on individual FAs and disease risk.

Longitudinal Associations Between Fat-Derived Dietary Patterns and Early Markers of Cardiovascular Disease Risk in the UK Biobank Study

Background Although the impact of dietary fats on cardiovascular disease (CVD) risk is widely researched, longitudinal associations between dietary patterns (DPs) based on fat type and early markers of CVD risk remain unclear. Methods and Results UK Biobank participants (46.9% men, mean age 55 years) with data on early markers of CVD risk (n=12 706) were followed longitudinally (2014-2020; mean 8.4 years). Two DPs (DP1, DP2) were derived using reduced rank regression (response variables: monounsaturated fat, polyunsaturated fat, and saturated fat based on two 24-hour dietary assessments. Multivariable logistic and linear regression were used to investigate associations between DPs and odds of elevated CVD risk (using the nonlaboratory Framingham Risk Score) and changes in early CVD markers, respectively. DP1 (characterized by higher nuts and seeds and lower fruit and legumes intake) was positively correlated with saturated fat, monounsaturated fat, and polyunsaturated fat; DP2 (characterized by higher butter and high-fat cheese, lower nuts and seeds intake) was positively correlated with saturated fat and negatively with polyunsaturated fat and monounsaturated fat. DP2 was associated with slightly higher odds of elevated CVD risk (odds ratio, 1.04 [95% CI, 1.00-1.07]). DP1 was associated with higher diastolic blood pressure (β, 0.20 [95% CI, 0.01-0.37]) and lower cardiac index (β, -0.02 [95% CI, -0.04 to -0.01]); DP2 was associated with higher carotid intima medial thickness (β, 1.80 [95% CI, 0.01-3.59]) and lower left ventricular ejection fraction (β, -0.15 [95% CI, -0.24 to -0.07]) and cardiac index (β, -0.01 [95% CI, -0.02 to -0.01]). Conclusions This study suggests small but statistically significant associations between DPs based on fat type and some early markers of CVD risk. Further research is needed to confirm these associations.

Associations Between Dietary Patterns and Incident Type 2 Diabetes: Prospective Cohort Study of 120,343 UK Biobank Participants

OBJECTIVE

To identify dietary patterns (DPs) characterized by a set of nutrients of concern and their association with incident type 2 diabetes (T2D).

RESEARCH DESIGN AND METHODS

A total of 120,343 participants from the U.K. Biobank study with at least two 24 h dietary assessments were studied. Reduced rank regression was used to derive DPs explaining variability in energy density, free sugars, saturated fat, and fiber intakes. We investigated prospective associations with T2D using Cox proportional hazard models.

RESULTS

Over 8.4 years of follow-up from the latest dietary assessment, 2,878 participants developed T2D. Two DPs were identified that jointly explained a total of 63% variation in four nutrients. DP1 was characterized by high intakes of chocolate and confectionery, butter, low-fiber bread, and sugars and preserves, and low intakes of fruits and vegetables. DP1 was linearly associated with T2D in multivariable models without BMI adjustment (per z score, hazard ratio [HR] 1.11 [95% CI 1.08-1.14]) and after BMI adjustment (HR 1.09 [95% CI 1.06-1.12]). DP2 was characterized by high intakes of sugar-sweetened beverages, fruit juice, table sugars and preserves, and low intakes of high-fat cheese and butter, but showed no clear association with T2D. There were significant interactions between both DPs and age, with increased risks among younger people in DP1 (HR 1.13 [95% CI 1.09-1.18]) and DP2 (HR 1.10 [95% CI 1.05-1.15]), as well as with DP1 and BMI, with increased risks among people with obesity (HR 1.11 [95% CI 1.07-1.16]).

CONCLUSIONS

A DP characterized by high intakes of chocolate and confectionery, butter, low-fiber bread, and added sugars, and low in fresh fruits and vegetables intake is associated with a higher incidence of T2D, particularly among younger people and those with obesity.

Dietary Patterns Characterized by Fat Type in Association with Obesity and Type 2 Diabetes: A Longitudinal Study of UK Biobank Participants

BACKGROUND

The fat type consumed is considered a risk factor for developing obesity and type 2 diabetes (T2D). However, these associations have not been investigated using a dietary patterns approach, which can capture combinations of foods and fat type consumed.

OBJECTIVES

This study aimed to investigate associations between dietary patterns with varying proportions of SFAs, MUFAs, or PUFAs and obesity, abdominal obesity, and self-reported T2D incidence.

METHODS

This study included UK Biobank participants with 2 or more 24-h dietary assessments, free from the outcome of interest at recruitment, and with outcome data at follow-up (n = 16,523; mean follow-up: 6.3 y). Reduced rank regression was used to derive dietary patterns with SFAs, MUFAs, and PUFAs (% of energy intake) as response variables. Logistic regression, adjusted for sociodemographic and health characteristics, was used to investigate the associations between dietary patterns and obesity [BMI (kg/m2) ≥30], abdominal obesity (waist circumference; men: ≥102 cm; women: ≥88 cm) and T2D incidence.

RESULTS

Two dietary patterns, DP1 and DP2, were identified: DP1 positively correlated with SFAs (r = 0.48), MUFAs (r = 0.67), and PUFAs (r = 0.56), characterized by higher intake of nuts, seeds, and butter and lower intake of fruit and low-fat yogurt; DP2 positively correlated with SFAs (r = 0.76) and negatively with PUFAs (r = -0.64) and MUFAs (r = -0.01), characterized by higher intake of butter and high-fat cheese and lower intake of nuts and seeds. Only DP2 was associated with higher obesity and abdominal obesity incidence (OR: 1.24; 95% CI: 1.02, 1.45; and OR: 1.19; 95% CI: 1.02, 1.38, respectively). Neither of the dietary patterns was associated with T2D incidence.

CONCLUSIONS

These findings provide evidence that a dietary pattern characterized by higher SFA and lower PUFA foods is associated with obesity and abdominal obesity incidence, but not T2D.

Describing a new food group classification system for UK biobank: analysis of food groups and sources of macro- and micronutrients in 208,200 participants

PURPOSE

The UK Biobank study collected detailed dietary data using a web-based self-administered 24 h assessment tool, the Oxford WebQ. We aimed to describe a comprehensive food grouping system for this questionnaire and to report dietary intakes and key sources of selected nutrients by sex and education.

METHODS

Participants with at least one valid 24-h questionnaire were included (n = 208,200). Dietary data were grouped based on the presence of nutrients as well as culinary use, processing, and plant/animal origin. For each food group, we calculated the contribution to energy intake, key macronutrients, and micronutrients. We also identified the top contributors to energy intake, free sugars and saturated fat by sex and education.

RESULTS

From the 93 food groups, the top five contributors to energy intake (in descending order) were: desserts/cakes/pastries; white bread; white pasta/rice; bananas/other fruit; semi-skimmed milk. Wine, beer, and fruit juices were the top beverage contributors to overall energy intake. Biscuits, and desserts/cakes/pastries were the highest contributors to free sugars, total fat, and saturated fat intakes, but also contributed to the calcium and iron intakes. Top contributors to energy, saturated fat, and free sugars were broadly similar by sex and education category, with small differences in average nutrient intakes across the population.

CONCLUSION

This new food classification system will support the growing interest in the associations between food groups and health outcomes and the development of food-based dietary guidelines. Food group variables will be available to all users of the UK Biobank WebQ questionnaire.

Associations Between Macronutrients From Different Dietary Sources and Serum Lipids in 24 639 UK Biobank Study Participants

[Figure: see text].

Associations of circulating insulin-like growth factor-I with intake of dietary proteins and other macronutrients

BACKGROUND & AIMS

Circulating insulin-like growth factor-I (IGF-I) is associated with the risk of several cancers. Dietary protein intake, particularly dairy protein, may increase circulating IGF-I; however, associations with different protein sources, other macronutrients, and fibre are inconclusive. To investigate the associations between intake of protein, macronutrients and their sources, fibre, and alcohol with serum IGF-I concentrations.

METHODS

A total of 11,815 participants from UK Biobank who completed ≥4 24-h dietary assessments and had serum IGF-I concentrations measured at baseline were included. Multivariable linear regression was used to assess the cross-sectional associations of macronutrient and fibre intake with circulating IGF-I concentrations.

RESULTS

Circulating IGF-I concentrations were positively associated with intake of total protein (per 2.5% higher energy intake: 0.56 nmol/L (95% confidence interval: 0.47, 0.66)), milk protein: 1.20 nmol/L (0.90, 1.51), and yogurt protein: 1.33 nmol/L (0.79, 1.86), but not with cheese protein: -0.07 nmol/L (-0.40, 0.25). IGF-I concentrations were also positively associated with intake of fibre (per 5 g/day higher intake: 0.46 nmol/L (0.35, 0.57)) and starch from wholegrains (Q5 vs. Q1: 1.08 nmol/L (0.77, 1.39)), and inversely associated with alcohol consumption (>40 g/day vs <1 g/day: -1.36 nmol/L (-1.00, -1.71)).

CONCLUSIONS

These results show differing associations with IGF-I concentrations depending on the source of dairy protein, with positive associations with milk and yogurt protein intake but no association with cheese protein. The positive association of fibre and starch from wholegrains with IGF-I warrants further investigation.

Adherence to international dietary recommendations in association with all-cause mortality and fatal and non-fatal cardiovascular disease risk: a prospective analysis of UK Biobank participants

BACKGROUND

International dietary guidelines aim to reduce risks of all-cause mortality, cardiovascular disease (CVD), and fatal CVD often associated with poor dietary habits. However, most studies have examined associations with individual nutrients, foods, or dietary patterns, as opposed to quantifying the pooled health effects of adherence to international dietary recommendations. We investigated associations between total adherence to the World Health Organization (WHO) dietary recommendations for saturated fats, free sugars, fibre, and fruits and vegetables and all-cause mortality and fatal and non-fatal CVD.

METHODS

We included participants from the UK Biobank cohort recruited in 2006-2010, which provided at least two valid 24-h dietary assessments. We defined adherence to dietary recommendations as ≤ 10% saturated fats, ≤ 10% free sugars, ≥ 25 g/day fibre, and ≥ 5 servings of fruits and vegetables/day. Multivariable Cox-proportional hazards models were used to investigate prospective associations with all-cause mortality and fatal and non-fatal CVD. In cross-sectional analyses, multivariable linear regression was used to examine associations with cardiometabolic risk factors.

RESULTS

Among 115,051 participants (39-72 years), only 29.7%, 38.5%, 22.3%, and 9.5% met 0, 1, 2, or 3-4 recommendations, respectively. There was a lower risk of all-cause mortality among participants meeting more dietary recommendations (Ptrend < 0.001), with a significantly lower risk among participants meeting 2: HR 0.91 (95% confidence interval [CI] 0.85-0.97) and 3-4: HR 0.79 (95% CI 0.71-0.88) recommendations. There was no trend with CVD risk, but a significantly lower risk of fatal CVD with 3-4 recommendations: HR 0.78 (95% CI 0.61-0.98). Meeting more recommendations resulted in significant cross-sectional trends (Ptrend < 0.001) towards lower body fat, waist circumference, LDL cholesterol, apolipoprotein B, triglycerides, alkaline phosphatase, gamma glutammyltransferase, and hs-CRP, but higher glucose and aspartate aminotransferase.

CONCLUSIONS

Meeting dietary recommendations is associated with additive reductions in premature mortality. Motivating and supporting people to adhere to dietary guidelines may help extend years of healthy life expectancy.