This study examined the relationship between childhood diet quality and arterial stiffness and thickness during adolescence/early adulthood. Participants were from the Avon Longitudinal Study of Parents and Children (ALSPAC) with dietary data at ages 7, 10 and 13 years and pulse wave velocity (PWV) and carotid intima-media thickness (cIMT) at ages 17 and/or 24 years. Diet quality (DQ) was assessed using five scores: a children’s Mediterranean-style diet (C-rMED) Z-score, a children’s Dietary Inflammatory Z-score (C-DIS), a DASH diet Z-score, a children’s Eatwell Guide (C-EWG) Z-score reflecting UK dietary guidelines and a data-driven obesogenic Z-score. Adjusted regression models examined the associations between DQ scores at 7–13 years and PWV and cIMT at 17 and 24 years. In adjusted models, a high v. low Obesogenic Z-score at 7 and 10 years was associated with higher PWV at 17: β 0.07 (95 % CI 0.01, 0.13) and β 0.10 (95 % CI 0.04, 0.16), respectively. A high v. low C-rMED Z-score at 7 years was associated with lower PWV at 17 (β −0.07; 95 % CI −0.14, −0.01). A high (more anti-inflammatory) vs low C-DIS Z-score at 10 years was associated with a lower PWV at 17 years: β −0.06 (95 % CI −0.12, −0.01). No other associations were observed. In conclusion, an Obesogenic dietary pattern in childhood (7–10 years) was related to increased arterial stiffness, while Mediterranean-style and anti-inflammatory diets were related to decreased arterial stiffness in adolescence. This highlights the importance of establishing healthy dietary habits early in life to protect against vascular damage.

Relatively little is known about how the diet of chronically undernourished children may impact cardiometabolic biomarkers. The objective of this exploratory study was to characterise relationships between dietary patterns and the cardiometabolic profile of 153 3–5-year-old Peruvian children with a high prevalence of chronic undernutrition. We collected monthly dietary recalls from children when they were 9–24 months old. At 3–5 years, additional dietary recalls were collected, and blood pressure, height, weight, subscapular skinfolds and fasting plasma glucose, insulin and lipid profiles were assessed. Nutrient intakes were expressed as average density per 100 kcals (i) from 9 to 24 months and (ii) at follow-up. The treelet transform and sparse reduced rank regress'ion (RRR) were used to summarize nutrient intake data. Linear regression models were then used to compare these factors to cardiometabolic outcomes and anthropometry. Linear regression models adjusting for subscapular skinfold-for-age Z-scores (SSFZ) were then used to test whether observed relationships were mediated by body composition. 26 % of children were stunted at 3–5 years old. Both treelet transform and sparse RRR-derived child dietary factors are related to protein intake and associated with total cholesterol and SSFZ. Associations between dietary factors and insulin were attenuated after adjusting for SSFZ, suggesting that body composition mediated these relationships. Dietary factors in early childhood, influenced by protein intake, are associated with cholesterol profiles, fasting glucose and body fat in a chronically undernourished population.

Most current nutrition policies and dietary recommendations still reflect decades of research addressing the mechanism of action or health risks of individual nutrients. Yet, most high-income countries including the UK are far from reaching the dietary intakes which are recommended for good health. Food-based dietary patterns (DPs) can help target specific combinations of foods that are associated with disease risk, recognising the coexistence of multiple nutrients within foods and their potential synergistic effects. Reduced rank regression (RRR) has emerged as a useful exploratory approach which uses a priori knowledge of the pathway from diet to disease to help identify DPs which are associated with disease risk in a particular population. Here we reviewed the literature with a focus on longitudinal cohort studies using RRR to derive DPs and reporting associations with non-communicable disease risk. We also illustrated the application of the RRR approach using data from the UK Biobank study, where we derived DPs that explained high variability in a set of nutrient response variables. The main DP was characterised by high intakes of chocolate and confectionery, butter and low-fibre bread, and low intakes of fresh fruit and vegetables and showed particularly strong associations with CVD, type 2 diabetes and all-cause mortality, which is consistent with previous studies that derived ‘Western’ or unhealthy DPs. These recent studies conducted in the UK Biobank population together with evidence from previous cohort studies contribute to the emerging evidence base to underpin food-based dietary advice for non-communicable disease prevention.

In recent decades, different data-driven approaches have emerged to identify dietary patterns (DP) and little is discussed about how these methods are able to capture diet complexity within the same population. This study aimed to apply three statistical methods to identify the DP of the Longitudinal Study of Adult Health (ELSA-Brasil) population and evaluate the similarities and differences between them. Dietary data were assessed at baseline in the ELSA-Brasil study using a FFQ. DP were identified by applying three statistical methods: (1) factor analysis (FA), (2) treelet transform (TT) and (3) reduced rank regression (RRR). The characteristics of individuals classified in the last tertile of each DP were compared. Cross-classification and Pearson’s correlation coefficients were assessed to evaluate the agreement between individuals’ adherence to DP of the three methods. A similar convenience DP was identified for all three methods. FA and TT also identified a similar prudent DP and a DP highly loaded for the food groups rice and beans. Individuals classified in the third tertile of similar DP of each method presented similar socio-demographic and nutrient intake characteristics. Regarding the cross-classification, prudent DP from FA and TT presented a higher level of agreement (75 %), while convenience DP from TT and RRR presented the lowest agreement (44·8 %). The different statistical methods were able to capture the populations’ DP in a similar way while highlighting the particularities of each method.

Hyperinsulinaemia and insulin resistance have been proposed to be associated with mortality risk, and diet can modulate insulin response. However, whether dietary patterns with high insulinaemic potential are associated with mortality remains unknown. We prospectively examined the associations between hyperinsulinaemic diets and the risk of total and cause-specific mortality in a large nationally representative population. Dietary factors were assessed by 24-h recalls. Two empirical dietary indices for hyperinsulinaemia (EDIH) and insulin resistance (EDIR) were developed to identify food groups most predictive of biomarkers for hyperinsulinaemia (C-peptide and insulin) and insulin resistance (homoeostatic model assessment for insulin resistance), respectively. Deaths from date of the first dietary interview until 31 December 2015 were identified by the National Death Index. Multivariable hazard ratios (HR) and 95 % CI were calculated using Cox regression models. During a median follow-up of 7·8 years, 4904 deaths were documented among 40 074 participants. For EDIH, the multivariable-adjusted HR (comparing extreme quintiles) were 1·20 (95 % CI 1·09, 1·32, P-trend<0·001) for overall mortality and 1·41 (95 % CI 1·15, 1·74, P-trend = 0·002) for CVD mortality. Similar associations were observed for EDIR with HR of 1·18 (95 % CI 1·07, 1·29, P-trend < 0·001) for total and 1·35 (95 % CI 1·09, 1·67, P-trend = 0·005) for CVD mortality. After further adjustments for BMI and diabetes, these positive associations were somewhat attenuated. Our findings suggested that diets with higher insulinaemic potential are associated with increased risk of overall and CVD-specific mortality.

The present study aimed to explore the association between dietary patterns in abdominal obesity obtained by reduced-rank regression (RRR) with visceral fat index (VFI) as a dependent variable and dyslipidemia in rural adults in Henan, China. A total of 29538 people aged 18–79 were selected from the Henan Rural Cohort Study. RRR analysis was used to identify dietary patterns; logistic regression analysis and restricted cubic spline regression models were applied to analyze the association between dietary patterns in abdominal obesity and dyslipidemia. VFI was used as a mediator to estimate the mediation effect. The dietary pattern in abdominal obesity was characterized by high carbohydrate and red meat intake and low consumption of fresh fruits, vegetables, milk, etc. After full adjustment, the highest quartile of dietary pattern scores was significantly associated with an increased risk of dyslipidemia (OR: 1·33, 95 % CI 1·23–1·44, P trend < 0·001), there was a non-linear dose–response relationship between them (P overall-association < 0·001, P non-lin-association = 0·022). The result was similar in dose-response between the dietary pattern scores and VFI. The indirect effect partially mediated by VFI was significant (OR: 1·07, 95 % CI 1·06–1·08). VIF explained approximately 53·3 % of odds of dyslipidemia related to the dietary pattern. Abdominal obesity dietary pattern scores positively affected VFI and dyslipidemia; there was a dose-response in both relationships. Dyslipidemia progression increased with higher abdominal obesity dietary pattern scores. In addition, VFI played a partial mediating role in relationship between abdominal obesity dietary pattern and dyslipidemia.

Inflammation is a central mechanism in metabolic disorders associated with morbidity and mortality and dietary factors can modulate inflammation. We aimed to prospectively investigate the association between an empirically developed, food-based dietary inflammatory pattern (EDIP) score and the risk of overall and cause-specific mortality, using data from the US National Health and Nutrition Examination Survey from 1999 to 2014. EDIP score was derived by entering thirty-nine predefined commonly consumed food groups into the reduced rank regression models followed by stepwise linear regression, which was most predictive of two plasma inflammation biomarkers including C-reactive protein and leucocyte count among 25 500 US adults. This score was further validated in a testing set of 9466 adults. Deaths from baseline until 31 December 2015 were identified through record linkage to the National Death Index. During a median follow-up of 7·8 years among 40 074 participants, we documented 4904 deaths. Compared with participants in the lowest quintile of EDIP score, those in the highest quintile had a higher risk of overall death (hazard ratio (HR) = 1·19, 95 % CI 1·08, 1·32, Ptrend = 0·002), and deaths from cancer (HR = 1·41, 95 % CI 1·14, 1·74, Ptrend = 0·017) and CVD (HR = 1·22, 95 % CI 0·98, 1·53, Ptrend = 0·211). When stratified by age, the association of EDIP with overall mortality was stronger among individuals under 65 years of age (Pinteraction = 0·001). Diets with a higher inflammatory potential were associated with increased risk of overall and cancer-specific mortality. Interventions to reduce the adverse effect of pro-inflammatory diets may potentially promote health and longevity.

The long-term inflammatory impact of diet could potentially elevate the risk of periodontal disease through modification of systemic inflammation. The aim of the present study was to prospectively investigate the associations between a food-based, reduced rank regression (RRR)-derived, empirical dietary inflammatory pattern (EDIP) and incidence of periodontitis. The study population was composed of 34 940 men from the Health Professionals Follow-Up Study, who were free of periodontal disease and major illnesses at baseline (1986). Participants provided medical and dental history through mailed questionnaires every 2 years and dietary data through validated semi-quantitative FFQ every 4 years. We used Cox proportional hazard models to examine the associations between EDIP scores and validated self-reported incidence of periodontal disease over a 24-year follow-up period. No overall association between EDIP and the risk of periodontitis was observed; the hazard ratio comparing the highest EDIP quintile (most proinflammatory diet) with the lowest quintile was 0·99 (95 % CI 0·89, 1·10, P-value for trend = 0·97). A secondary analysis showed that among obese non-smokers (i.e. never and former smokers at baseline), the hazard ratio for periodontitis comparing the highest EDIP quintile with the lowest was 1·39 (95 % CI 0·98, 1·96, P-value for trend = 0·03). In conclusion, no overall association was detected between EDIP and incidence of self-reported periodontitis in the study population. From the subgroups evaluated, EDIP was significantly associated with increased risk of periodontitis only among non-smokers who were obese. Hence, this association must be interpreted with caution.

The impact of diet on the metabolic syndrome (MetS) and CVD has been investigated widely, but few studies have investigated the association between dietary patterns (DP) and the predicted CVD, derived from reduced rank regression (RRR). The objectives of this study were to derive DP using RRR and principal component analysis (PCA) and investigate their associations with the MetS and estimated 10-year atherosclerotic CVD (ASCVD). We used the baseline dataset from the Xinjiang multi-ethnic cohort study in China, collected from June 2018 to May 2019. A total of 14 982 subjects aged 35–74 years from Urumqi, Huo Cheng and Mo Yu were included in the analysis. The 10-year ASCVD risk was estimated using the Chinese ASCVD risk equations. The associations of DP with the MetS and 10-year ASCVD were determined using multivariable logistic regression models. In Urumqi and Mo Yu, the increased RRR DP score was associated with a higher OR of having the MetS and with a higher OR of elevated 10-year ASCVD risk. However, only the first DP determined by PCA in Urumqi was inversely associated with the MetS and elevated 10-year ASCVD risk. The prevalence of the MetS and elevated ASCVD risk in urban population is higher than that in rural areas. Our results may help nutritionists develop more targeted dietary strategies to prevent the MetS and ASCVD in different regions in China.

High protein intake in young children is associated with excess gains in weight and body fat, but the specific role of different protein sources has yet to be described. The study aimed to investigate the role of different types of protein in the post-weaning stage on weight, BMI and overweight/obesity at 60 months. Intakes of animal, dairy and plant protein and a dietary pattern characterising variation in protein types at 21 months of age were estimated using a 3-d diet diary in a cohort of 2154 twins; weight and height were recorded every 3 months from birth to 60 months. Longitudinal mixed-effect models investigated the associations between sources of protein intake or dietary pattern scores and BMI, weight and overweight/obesity from 21 months up to 60 months. Adjusting for confounders, dairy protein intake at 21 months was positively associated with greater weight (46 (95 % CI 21, 71) g and BMI up to 60 months (0·04 (95 % CI 0·004, 0·070) kg/m2) and the odds of overweight/obesity at 3 years (OR 1·12; 95 % CI 1·00, 1·24). Milk showed associations of similar magnitude. A dietary pattern low in dairy protein and high in plant protein was associated with lower weight gain up to 60 months, but not overweight/obesity. Intake of dairy products in early childhood is most strongly associated with weight gain, compared with other protein sources. A dietary pattern characterised by lower protein intake and greater protein source diversity at 2 years may confer a lower risk of excess weight gain.

Besides a priori approaches, using previous knowledge about food characteristics, exploratory dietary pattern (DP) methods, using data at hand, are commonly applied. This systematic literature review aimed to identify exploratory methods on DP in pan-European studies and to inform the development of the DEterminants of DIet and Physical ACtivity (DEDIPAC) toolbox of methods suitable for use in future European studies. The search was conducted in three databases on prospective studies in healthy, free-living people across the whole life span. To identify validated DP methods, an additional search without regional restrictions was conducted. Studies including at least two European countries were retained. The search resulted in six pan-European studies applying principal component/factor analysis (PC/FA) (n 5) or cluster analysis (n 2). The criteria to retain PC/factors ranged from the application of the eigenvalue>1 criterion, the scree plot and/or the interpretability criterion. Furthermore, seven validation studies were identified: DP, derived by PC/FA (n 6) or reduced rank regression (RRR) (n 1) were compared using dietary information from FFQ (n 6) or dietary history (n 1) as study instrument and dietary records (n 6) or 24-h dietary recalls (n 1) as reference. The correlation coefficients for the derived DP ranged from modest to high. To conclude, PC/FA was predominantly applied using the eigenvalue criterion and scree plot to retain DP, but a better description of the applied criteria is highly recommended to enable a standardised application of the method. Research gaps were identified for the methods cluster analysis and RRR, as well as for validation studies on DP.

The aim of this study was to derive dietary patterns associated with cardio-metabolic traits and to examine whether these predict prospective changes in these traits and incidence of the metabolic syndrome (iMetS). Subjects from the Malmö Diet and Cancer Study cardiovascular cohort without cardio-metabolic disease and related drug treatments at baseline (n 4071; aged 45–67 years, 40 % men) were included. We applied reduced rank regression on thirty-eight foods to derive patterns that explain variation in response variables measured at baseline (waist circumference, TAG, HDL- and LDL-cholesterol, systolic and diastolic blood pressure, fasting glucose and insulin). Patterns were examined in relation to change in cardio-metabolic traits and iMetS in subjects who were re-examined after 16·7 years (n 2704). Two dietary patterns (‘Western’ and ‘Drinker’) were retained and explained 3·2 % of the variation in response variables. The ‘Western’ dietary pattern was inversely associated with HDL-cholesterol and positively with all other response variables (both at baseline and follow-up), but there was no association with LDL at follow-up. After adjustment for potential confounders, the ‘Western’ dietary pattern was associated with higher risk of iMetS (hazard ratio Q4 v. Q1: 1·47; 95 % CI 1·23, 1·77; Ptrend=1·5×10−5). The ‘Drinker’ dietary pattern primarily explained variation in HDL and was not associated with iMetS. In conclusion, this study supports current food-based dietary guidelines suggesting that a ‘Western’ dietary pattern with high intakes of sugar-sweetened beverages and red and processed meats and low intakes of wine, cheese, vegetables and high-fibre foods is associated with detrimental effects on cardio-metabolic health.

This study aims to examine repeatability of reduced rank regression (RRR) methods in calculating dietary patterns (DP) and cross-sectional associations with overweight (OW)/obesity across European and Australian samples of adolescents. Data from two cross-sectional surveys in Europe (2006/2007 Healthy Lifestyle in Europe by Nutrition in Adolescence study, including 1954 adolescents, 12–17 years) and Australia (2007 National Children’s Nutrition and Physical Activity Survey, including 1498 adolescents, 12–16 years) were used. Dietary intake was measured using two non-consecutive, 24-h recalls. RRR was used to identify DP using dietary energy density, fibre density and percentage of energy intake from fat as the intermediate variables. Associations between DP scores and body mass/fat were examined using multivariable linear and logistic regression as appropriate, stratified by sex. The first DP extracted (labelled ‘energy dense, high fat, low fibre’) explained 47 and 31 % of the response variation in Australian and European adolescents, respectively. It was similar for European and Australian adolescents and characterised by higher consumption of biscuits/cakes, chocolate/confectionery, crisps/savoury snacks, sugar-sweetened beverages, and lower consumption of yogurt, high-fibre bread, vegetables and fresh fruit. DP scores were inversely associated with BMI z-scores in Australian adolescent boys and borderline inverse in European adolescent boys (so as with %BF). Similarly, a lower likelihood for OW in boys was observed with higher DP scores in both surveys. No such relationships were observed in adolescent girls. In conclusion, the DP identified in this cross-country study was comparable for European and Australian adolescents, demonstrating robustness of the RRR method in calculating DP among populations. However, longitudinal designs are more relevant when studying diet–obesity associations, to prevent reverse causality.

Evidence linking dietary patterns (DP) and obesity and hypertension prevalence is inconsistent. We aimed to identify DP derived from energy density, fibre and sugar intakes, as well as Na, K, fibre, SFA and PUFA, and investigate associations with obesity and hypertension. Adults (n 4908) were included from the cross-sectional Australian Health Survey 2011–2013. Two 24-h dietary recalls estimated food and nutrient intakes. Reduced rank regression derived DP with dietary energy density (DED), fibre density and total sugar intake as response variables for obesity and Na:K, SFA:PUFA and fibre density as variables for hypertension. Poisson regression investigated relationships between DP and prevalence ratios (PR) of overweight/obesity (BMI≥25 kg/m2) and hypertension (blood pressure≥140/90 mmHg). Obesity-DP1 was positively correlated with fibre density and sugars and inversely with DED. Obesity-DP2 was positively correlated with sugars and inversely with fibre density. Individuals in the highest tertile of Obesity-DP1 and Obesity-DP2, compared with the lowest, had lower (PR 0·88; 95 % CI 0·81, 0·95) and higher (PR 1·09; 95 % CI 1·01, 1·18) prevalence of obesity, respectively. Na:K and SFA:PUFA were positively correlated with Hypertension-DP1 and inversely correlated with Hypertension-DP2, respectively. There was a trend towards higher hypertension prevalence in the highest tertile of Hypertension-DP1 compared with the lowest (PR 1·18; 95 % CI 0·99, 1·41). Hypertension-DP2 was not associated with hypertension. Obesity prevalence was inversely associated with low-DED, high-fibre and high-sugar (natural sugars) diets and positively associated with low-fibre and high-sugar (added sugars) diets. Hypertension prevalence was higher on low-fibre and high-Na and SFA diets.

This study aimed to identify dietary patterns using reduced rank regression (RRR) and to explore their associations with depressive symptoms over 9 years in the Invecchiare in Chianti study. At baseline, 1362 participants (55·4 % women) aged 18–102 years (mean age 68 (sd 15·5) years) were included in the study. Baseline data collection started in 1998 and was repeated after 3, 6 and 9 years. Dietary intake information was obtained using a country-specific, validated FFQ with 188 food items. For baseline diet, dietary pattern scores in quartiles (Q) were derived using RRR with the nutrients EPA+DHA, folate, Mg and Zn as response variables. Continuous depression scores from the Centre for Epidemiologic Studies Depression (CES-D) scale were used for assessing depressive symptoms. The derived dietary pattern was rich in vegetables, olive oil, grains, fruit, fish and moderate in wine and red and processed meat, and was labelled as ‘typical Tuscan dietary pattern’. After full adjustment, an inverse association was observed between this dietary pattern and depressive symptoms at baseline (Q1 v. Q4, B −2·77; 95 % CI −4·55, −0·98). When examining the relationship between the above-mentioned dietary pattern at baseline and depressive symptoms over 9 years, a similar association was found after full adjustment for confounding factors (Q1 v. Q4, B −1·78; 95 % CI −3·17, −0·38). A diet rich in vegetables, olive oil, grains, fruits, fish and moderate in wine and red and processed meat was consistently associated with lower CES-D scores over a 9-year period in the Tuscan population.

The combined association of dietary fat, glycaemic index (GI) and fibre with type 2 diabetes has rarely been investigated. The objective was to examine the relationship between a high-fat, high-GI, low-fibre dietary pattern across adult life and type 2 diabetes risk using reduced rank regression. Data were from the MRC National Survey of Health and Development. Repeated measures of dietary intake estimated using 5-d diet diaries were available at the age of 36, 43 and 53 years for 1180 study members. Associations between dietary pattern scores at each age, as well as longitudinal changes in dietary pattern z-scores, and type 2 diabetes incidence (n 106) from 53 to 60–64 years were analysed. The high-fat, high-GI, low-fibre dietary pattern was characterised by low intakes of fruit, vegetables, low-fat dairy products and whole-grain cereals, and high intakes of white bread, fried potatoes, processed meat and animal fats. There was an increasing trend in OR for type 2 diabetes with increasing quintile of dietary pattern z-scores at the age of 43 years among women but not among men. Women in the highest z-score quintile at the age of 43 years had an OR for type 2 diabetes of 5·45 (95 % CI 2·01, 14·79). Long-term increases in this dietary pattern, independently of BMI and waist circumference, were also detrimental among women: for each 1 sd unit increase in dietary pattern z-score between 36 and 53 years, the OR for type 2 diabetes was 1·67 (95 % CI 1·20, 2·43) independently of changes in BMI and waist circumference in the same periods. A high-fat, high-GI, low-fibre dietary pattern was associated with increased type 2 diabetes risk in middle-aged British women but not in men.

Primary school years seem to represent a critical period for the development of overweight and obesity. However, only a few studies have analysed the prospective relationship between dietary patterns and weight status in children. The aims of the present study were to identify dietary patterns at the beginning of and during the primary school period and to examine their relevance to the development of body composition. Nutritional and anthropometric data from 371 participants of the Dortmund Nutritional and Longitudinally Designed (DONALD) Study at the beginning (ages 6 and 7 years) and end (ages 10 and 11 years) of the primary school period were used. Principal component analyses (PCA) were conducted to identify dietary patterns, which were regressed on changes in BMI and fat mass index (FMI) between ages 6 and 7 years and ages 10 and 11 years. Reduced rank regression (RRR) was used to directly extract patterns explaining variation in changes in BMI and FMI between ages 6 and 7 years and ages 10 and 11 years. PCA yielded interpretable patterns of dietary changes at the beginning of and during the primary school period, which were not related to changes in body composition. Conversely, RRR allowed identifying predictive patterns: higher baseline intakes of white bread and lower baseline intakes of whole-grain products as well as increases in the consumption of savoury snacks, sausages and cheese during primary school years independently predicted increases in BMI and FMI during the primary school period. In conclusion, selection of unfavourable carbohydrate sources at the beginning of the primary school period and increases in the consumption of processed savoury foods during primary school years may adversely affect the development of body composition during the course of primary school.