Dairy products and cardio-metabolic health: aspects from nutritional, molecular and genetic epidemiology

There is accumulating evidence on differences in the link between types of dairy products and cardio-metabolic health, but inconsistent findings limit the field. In my PhD project, I undertook an epidemiological investigation comprising inter-related but distinct themes evaluating aspects of nutritional, molecular and genetic epidemiology to advance scientific understanding. I undertook research to describe dairy consumption patterns over time by evaluating nationally-representative data of the United Kingdom National Diet and Nutrition Survey. I observed significant time trends for specific dairy types and groups, which were different among different groups of people e.g. adults younger than 65 years or elderly people. Using data from the large Fenland (n~12,000) and EPIC Norfolk (n~25,000) studies, I investigated associations of total and types of dairy consumption with markers of metabolic risk and adiposity as potential pathways to cardio-metabolic disease. The analyses showed differential associations of dairy types and groups mainly with markers of adiposity and lipidaemia. I explored the potential of objective markers to assess dairy consumption, by examining metabolomics profiles and blood fatty acids to identify a set of biomarkers predicting dairy consumption and prospective associations of the identified biomarkers with type 2 diabetes risk. I was able to develop and validate metabolite scores reflecting consumption of some dairy products and observed inverse associations between some of these scores and type 2 diabetes incidence. I analysed genetic determinants of dairy consumption, using a genome-wide association study in the UK Biobank (n~500,000) and identified single nucleotide polymorphisms predicting milk, cheese and total dairy consumption. Overall, this PhD work contributed towards (1) a more precise description of dairy consumption patterns in the UK, (2) hypothesis formulation for potential biological pathways linking to cardio-metabolic disease, (3) discovery of metabolite scores as potential dairy biomarkers and (4) hypothesis formulation for potential genetic predictors of dairy consumption

Associations of types of dairy consumption with adiposity: cross-sectional findings from over 12 000 adults in the Fenland Study, UK.

Evidence from randomised controlled trials supports beneficial effects of total dairy products on body weight, fat and lean mass, but evidence on associations of dairy types with distributions of body fat and lean mass is limited. We aimed to investigate associations of total and different types of dairy products with markers of adiposity, and body fat and lean mass distribution. We evaluated cross-sectional data from 12 065 adults aged 30-65 years recruited to the Fenland Study between 2005 and 2015 in Cambridgeshire, UK. Diet was assessed with an FFQ. We estimated regression coefficients (or percentage differences) and their 95 % CI using multiple linear regression models. The medians of milk, yogurt and cheese consumption were 293 (interquartile range (IQR) 146-439), 35·3 (IQR 8·8-71·8) and 14·6 (IQR 4·8-26·9) g/d, respectively. Low-fat dairy consumption was inversely associated with visceral:subcutaneous fat ratio estimated with dual-energy X-ray absorptiometry (-2·58 % (95 % CI -3·91, -1·23 %) per serving/d). Habitual consumption per serving/d (200 g) of milk was associated with 0·33 (95 % CI 0·19, 0·46) kg higher lean mass. Other associations were not significant after false discovery correction. Our findings suggest that the influence of milk consumption on lean mass and of low-fat dairy consumption on fat mass distribution may be potential pathways for the link between dairy consumption and metabolic risk. Our cross-sectional findings warrant further research in prospective and experimental studies in diverse populations.The Fenland study was funded by the Medical Research Council and the Wellcome Trust The current work was supported by the Medical Research Council (N.G.F., grant number MC_UU_12015/5), (N.J.W., grant number MC_UU_12015/1), (S.B., grant number MC_UU_12015/3); the National Institute of Health Research Cambridge (NIHR) Biomedical Research Centre (N.G.F., S.B., and N.J.W., grant number IS-BRC-1215-20014); and the Cambridge Trust (E.T.). The funders had no role in the design, analysis or writing of this article

Educational and social inequalities and cause-specific mortality in Mexico City: a prospective study

Background: Social inequalities in adult mortality have been reported across diverse populations, but there is no largescale prospective evidence from Mexico. We aimed to quantify social, including educational, inequalities in mortality among adults in Mexico City. Methods: The Mexico City Prospective Study recruited 150 000 adults aged 35 years and older from two districts of Mexico City between 1998 and 2004. Participants were followed up until Jan 1, 2021 for cause-specific mortality. Cox regression analysis yielded rate ratios (RRs) for death at ages 35–74 years associated with education and examined, in exploratory analyses, the mediating effects of lifestyle and related risk factors. Findings: Among 143 478 participants aged 35–74 years, there was a strong inverse association of education with premature death. Compared with participants with tertiary education, after adjustment for age and sex, those with no education had about twice the mortality rate (RR 1·84; 95% CI 1·71–1·98), equivalent to approximately 6 years lower life expectancy, with an RR of 1·78 (1·67–1·90) among participants with incomplete primary, 1·62 (1·53–1·72) with complete primary, and 1·34 (1·25–1·42) with secondary education. Education was most strongly associated with death from renal disease and acute diabetic crises (RR 3·65; 95% CI 3·05–4·38 for no education vs tertiary education) and from infectious diseases (2·67; 2·00–3·56), but there was an apparent higher rate of death from all specific causes studied with lower education, with the exception of cancer for which there was little association. Lifestyle factors (ie, smoking, alcohol drinking, and leisure time physical activity) and related physiological correlates (ie, adiposity, diabetes, and blood pressure) accounted for about four-fifths of the association of education with premature mortality. Interpretation: In this Mexican population there were marked educational inequalities in premature adult mortality, which appeared to largely be accounted for by lifestyle and related risk factors. Effective interventions to reduce these risk factors could reduce inequalities and have a major impact on premature mortality. Funding: Wellcome Trust, the Mexican Health Ministry, the National Council of Science and Technology for Mexico, Cancer Research UK, British Heart Foundation, and the UK Medical Research Council Population Health Research Unit

Effectiveness of school food environment policies on children's dietary behaviors: A systematic review and meta-analysis.

BACKGROUND: School food environment policies may be a critical tool to promote healthy diets in children, yet their effectiveness remains unclear. OBJECTIVE: To systematically review and quantify the impact of school food environment policies on dietary habits, adiposity, and metabolic risk in children. METHODS: We systematically searched online databases for randomized or quasi-experimental interventions assessing effects of school food environment policies on children's dietary habits, adiposity, or metabolic risk factors. Data were extracted independently and in duplicate, and pooled using inverse-variance random-effects meta-analysis. Habitual (within+outside school) dietary intakes were the primary outcome. Heterogeneity was explored using meta-regression and subgroup analysis. Funnel plots, Begg's and Egger's test evaluated potential publication bias. RESULTS: From 6,636 abstracts, 91 interventions (55 in US/Canada, 36 in Europe/New Zealand) were included, on direct provision of healthful foods/beverages (N = 39 studies), competitive food/beverage standards (N = 29), and school meal standards (N = 39) (some interventions assessed multiple policies). Direct provision policies, which largely targeted fruits and vegetables, increased consumption of fruits by 0.27 servings/d (n = 15 estimates (95%CI: 0.17, 0.36)) and combined fruits and vegetables by 0.28 servings/d (n = 16 (0.17, 0.40)); with a slight impact on vegetables (n = 11; 0.04 (0.01, 0.08)), and no effects on total calories (n = 6; -56 kcal/d (-174, 62)). In interventions targeting water, habitual intake was unchanged (n = 3; 0.33 glasses/d (-0.27, 0.93)). Competitive food/beverage standards reduced sugar-sweetened beverage intake by 0.18 servings/d (n = 3 (-0.31, -0.05)); and unhealthy snacks by 0.17 servings/d (n = 2 (-0.22, -0.13)), without effects on total calories (n = 5; -79 kcal/d (-179, 21)). School meal standards (mainly lunch) increased fruit intake (n = 2; 0.76 servings/d (0.37, 1.16)) and reduced total fat (-1.49%energy; n = 6 (-2.42, -0.57)), saturated fat (n = 4; -0.93%energy (-1.15, -0.70)) and sodium (n = 4; -170 mg/d (-242, -98)); but not total calories (n = 8; -38 kcal/d (-137, 62)). In 17 studies evaluating adiposity, significant decreases were generally not identified; few studies assessed metabolic factors (blood lipids/glucose/pressure), with mixed findings. Significant sources of heterogeneity or publication bias were not identified. CONCLUSIONS: Specific school food environment policies can improve targeted dietary behaviors; effects on adiposity and metabolic risk require further investigation. These findings inform ongoing policy discussions and debates on best practices to improve childhood dietary habits and health

Associations of circulating fatty acids with incident coronary heart disease: a prospective study of 89,242 individuals in UK Biobank

Background: the role of fatty acids in coronary heart disease (CHD) remains uncertain. There is little evidence from large-scale epidemiological studies on the relevance of circulating fatty acids levels to CHD risk. This study aims to examine the independent associations of the major circulating types of fatty acids with CHD risk.Methods: UK Biobank is a prospective study of adults aged 40–69 in 2006–2010; in 2012–2013, a subset of the participants were resurveyed. Analyses were restricted to 89,242 participants with baseline plasma fatty acids (measured using nuclear magnetic resonance spectroscopy) and without prior CHD. Cox proportional hazards models were used to estimate hazard ratios (HRs) for the associations with incidence CHD, defined as the first-ever myocardial infarction, unstable angina pectoris, coronary-related death, or relevant procedure. And the major types of fatty acids were mutually adjusted to examine the independent associations. Hazard ratios were corrected for regression dilution using the correlation of baseline and resurvey fatty acids measures.Results: during a median follow-up of 11.8 years, 3,815 incident cases of CHD occurred. Independently of other fatty acids, CHD risk was positively associated with saturated fatty acids (SFA) and monounsaturated fatty acids (MUFA), inversely associated with omega-3 polyunsaturated fatty acids (PUFA), but there was no strong evidence of an association with omega-6 PUFA: HR per standard deviation higher were 1.14 (95% CI, 1.09–1.20), 1.15 (1.10–1.21), 0.91 (0.87–0.94), and 1.04 (0.99–1.09) respectively. Independently of triglycerides and cholesterol, the inverse association with omega-3 PUFA was not materially changed, but the positive associations with SFA and MUFA attenuated to null after adjusting for triglycerides levels.Conclusions: this large-scale study has quantitated the independent associations of circulating fatty acids with CHD risk. Omega-3 PUFA was inversely related to CHD risk, independently of other fatty acids and major lipid fractions. By contrast, independently of other fatty acids, the positive associations of circulating SFA and MUFA with CHD risk were mostly attributed to their relationship with triglycerides

Predictive value of metabolic profiling in cardiovascular risk scores: analysis of 75 000 adults in UK Biobank

Background: metabolic profiling (the extensive measurement of circulating metabolites across multiple biological pathways) is increasingly employed in clinical care. However, there is little evidence on the benefit of metabolic profiling as compared with established atherosclerotic cardiovascular disease (CVD) risk scores.Methods: UK Biobank is a prospective study of 0.5 million participants, aged 40–69 at recruitment. Analyses were restricted to 74 780 participants with metabolic profiling (measured using nuclear magnetic resonance) and without CVD at baseline. Cox regression was used to compare model performance before and after addition of metabolites to QRISK3 (an established CVD risk score used in primary care in England); analyses derived three models, with metabolites selected by association significance or by employing two different machine learning approaches.Results: we identified 5097 incident CVD events within the 10-year follow-up. Harrell’s C-index of QRISK3 was 0.750 (95% CI 0.739 to 0.763) for women and 0.706 (95% CI 0.696 to 0.716) for men. Adding selected metabolites did not significantly improve measures of discrimination in women (Harrell’s C-index of three models are 0.759 (0.747 to 0.772), 0.759 (0.746 to 0.770) and 0.759 (0.748 to 0.771), respectively) or men (0.710 (0.701 to 0.720), 0.710 (0.700 to 0.719) and 0.710 (0.701 to 0.719), respectively), and neither did it improve reclassification or calibration.Conclusion: this large-scale study applied both conventional and machine learning approaches to assess the potential benefit of metabolic profiling to well-established CVD risk scores. However, there was no evidence that metabolic profiling improved CVD risk prediction in this population

Predictive value of circulating NMR metabolic biomarkers for type 2 diabetes risk in the UK Biobank study

Background Effective targeted prevention of type 2 diabetes (T2D) depends on accurate prediction of disease risk. We assessed the role of metabolomic profiling in improving T2D risk prediction beyond conventional risk factors. Methods Nuclear magnetic resonance (NMR) metabolomic profiling was undertaken on baseline plasma samples in 65,684 UK Biobank participants without diabetes and not taking lipid-lowering medication. Among a subset of 50,519 participants with data available on all relevant co-variates (sociodemographic characteristics, parental history of diabetes, lifestyle—including dietary—factors, anthropometric measures and fasting time), Cox regression yielded adjusted hazard ratios for the associations of 143 individual metabolic biomarkers (including lipids, lipoproteins, fatty acids, amino acids, ketone bodies and other low molecular weight metabolic biomarkers) and 11 metabolic biomarker principal components (PCs) (accounting for 90% of the total variance in individual biomarkers) with incident T2D. These 11 PCs were added to established models for T2D risk prediction among the full study population, and measures of risk discrimination (c-statistic) and reclassification (continuous net reclassification improvement [NRI], integrated discrimination index [IDI]) were assessed. Results During median 11.9 (IQR 11.1–12.6) years’ follow-up, after accounting for multiple testing, 90 metabolic biomarkers showed independent associations with T2D risk among 50,519 participants (1211 incident T2D cases) and 76 showed associations after additional adjustment for HbA1c (false discovery rate controlled p < 0.01). Overall, 8 metabolic biomarker PCs were independently associated with T2D. Among the full study population of 65,684 participants, of whom 1719 developed T2D, addition of PCs to an established risk prediction model, including age, sex, parental history of diabetes, body mass index and HbA1c, improved T2D risk prediction as assessed by the c-statistic (increased from 0.802 [95% CI 0.791–0.812] to 0.830 [0.822–0.841]), continuous NRI (0.44 [0.38–0.49]) and relative (15.0% [10.5–20.4%]) and absolute (1.5 [1.0–1.9]) IDI. More modest improvements were observed when metabolic biomarker PCs were added to a more comprehensive established T2D risk prediction model additionally including waist circumference, blood pressure and plasma lipid concentrations (c-statistic, 0.829 [0.819–0.838] to 0.837 [0.831–0.848]; continuous NRI, 0.22 [0.17–0.28]; relative IDI, 6.3% [4.1–9.8%]; absolute IDI, 0.7 [0.4–1.1]). Conclusions When added to conventional risk factors, circulating NMR-based metabolic biomarkers modestly enhanced T2D risk prediction

Lipoprotein characteristics and incident coronary heart disease: prospective cohort of nearly 90 000 individuals in UK Biobank

Background: associations of coronary heart disease (CHD) with plasma lipids are well described, but the associations with characteristics of lipoproteins (which transport lipids) remain unclear.Methods and Results: UK Biobank is a prospective study of 0.5 million adults. Analyses were restricted to 89 422 participants with plasma lipoprotein and apolipoprotein measures from Nightingale nuclear magnetic resonance spectroscopy and without CHD at baseline. CHD risk was positively associated with concentrations of very‐low‐density lipoproteins, intermediate‐density lipoproteins, and low‐density lipoproteins (LDL), and inversely associated with high‐density lipoproteins. Hazard ratios (99% CIs) per SD were 1.22 (1.17–1.28), 1.16 (1.11–1.21), 1.20 (1.15–1.25), and 0.90 (0.86–0.95), respectively. Larger subclasses of very‐low‐density lipoproteins were less strongly associated with CHD risk, but associations did not materially vary by size of LDL or high‐density lipoprotein. Given lipoprotein particle concentrations, lipid composition (including cholesterol) was not strongly related to CHD risk, except for triglyceride in LDL particles. Apolipoprotein B was highly correlated with LDL concentration (r=0.99), but after adjustment for apolipoprotein B, concentrations of very‐low‐density lipoprotein and high‐density lipoprotein particles remained strongly related to CHD risk.Conclusions: this large‐scale study reliably quantifies the associations of nuclear magnetic resonance–defined lipoprotein characteristics with CHD risk. CHD risk was most strongly related to particle concentrations, and separate measurements of lipoprotein concentrations may be of greater value than the measurement by apolipoprotein B, which was largely determined by LDL concentration alone. Furthermore, there was strong evidence of positive association with mean triglyceride molecules per LDL particle but little evidence of associations with total triglycerides or other lipid and lipoprotein fractions after accounting for lipoprotein concentrations

The associations of longitudinal changes in consumption of total and types of dairy products and markers of metabolic risk and adiposity: findings from the European Investigation into Cancer and Nutrition (EPIC)-Norfolk study, United Kingdom.

BACKGROUND: The consumption of some types of dairy products has been associated with lower cardiometabolic disease incidence. Knowledge remains limited about habitual dairy consumption and the pathways to cardiometabolic risk. OBJECTIVE: We aimed to investigate associations of habitual consumption of total and types of dairy products with markers of metabolic risk and adiposity among adults in the United Kingdom. METHODS: We examined associations of changes in dairy consumption (assessed with a food-frequency questionnaire) with parallel changes in cardiometabolic markers using multiple linear regression among 15,612 adults aged 40-78 y at baseline (1993-1997) and followed up over 1998-2000 (mean ± SD: 3.7±0.7 y) in the European Prospective Investigation into Cancer and Nutrition (EPIC)-Norfolk study. RESULTS: For adiposity, an increase in fermented dairy products [yogurt (total or low-fat) or low-fat cheese] consumption was associated with a lower increase in body weight and body mass index (BMI). For example, over 3.7 y, increasing yogurt consumption by 1 serving/d was associated with a smaller increase in body weight by 0.23 kg (95% CI: -0.46, -0.01 kg). An increase in full-fat milk, high-fat cheese, and total high-fat dairy was associated with greater increases in body weight and BMI [e.g., for high-fat dairy: β = 0.13 (0.05, 0.21) kg and 0.04 (0.01, 0.07) kg/m2, respectively]. For lipids, an increase in milk (total and low-fat) or yogurt consumption was positively associated with HDL cholesterol. An increase in total low-fat dairy was negatively associated with LDL cholesterol (-0.03 mmol/L; -0.05, -0.01 mmol/L), whereas high-fat dairy (total, butter, and high-fat cheese) consumption was positively associated [e.g., 0.04 (0.02, 0.06) mmol/L for total high-fat dairy]. For glycemia, increasing full-fat milk consumption was associated with a higher increase in glycated hemoglobin (P = 0.027). CONCLUSIONS: The habitual consumption of different dairy subtypes may differently influence cardiometabolic risk through adiposity and lipid pathways.The EPIC Norfolk study (DOI 10.22025/2019.10.105.00004) has received funding from the Medical Research Council (MR/N003284/1 and MC-UU_12015/1) and Cancer Research UK (C864/A14136). This work was supported by the Medical Research Council Epidemiology Unit core funding [MC_UU_12015/1 and MC_UU_12015/5]. NJW and NGF acknowledge support from the National Institute for Health Research Cambridge Biomedical Research Centre [IS-BRC-1215-20014] and NJW is an NIHR Senior Investigator. ET held a PhD scholarship from the Cambridge Trust and the Medical Research Council Epidemiology Unit