Modification Role of Dietary Antioxidants in the Association of High Red Meat Intake and Lung Cancer Risk: Evidence from a Cancer Screening Trial.

Evidence on the association between red meat consumption and lung cancer risk is weak. This study examined the associations between red meat and lung cancer across levels of antioxidant intake from foods or supplements. Cox proportional hazard models were applied to assess hazard ratios (HRs) for lung cancer incidence in the Prostate, Lung, Colorectal, and Ovarian (PLCO) cancer screening trial. Baseline food frequency questionnaires measured red meat and antioxidant intake. The food-based Composite Dietary Antioxidant Index (fCDAI) evaluated the overall natural intake of vitamin A, vitamin C, vitamin E, zinc, magnesium, and selenium. During 13 years of follow-up, 95,647 participants developed 1599 lung cancer cases. Higher red meat consumption was associated with a higher risk of lung cancer (HRQ4vsQ1 1.43, 95%CI 1.20-1.71, p-trend < 0.001). We observed similar trends across groups with low or medium levels of antioxidant intake. However, no association was noticed in the group with the highest fCDAI (HRQ4vsQ1 1.24, 95%CI 0.90-1.72, p-trend = 0.08) and highest independent natural antioxidant intake. The attenuated risk was not consistently observed among groups with high supplement use. Lastly, we did not notice evidence of interactions between red meat and antioxidant intake. Our findings emphasize the importance of limiting red meat in lung cancer prevention.

Development and validation of dietary depression index in Chinese adults.

Objective: Previous studies have suggested diet was associated with depressive symptoms. We aimed to develop and validate Dietary Depression Index (DDI) based on dietary prediction of depression in a large Chinese cancer screening cohort.Methods: In the training set (n = 2729), we developed DDI by using intake of 20 food groups derived from a food frequency questionnaire to predict depression as assessed by Patient Health Questionnaire-9 based on the reduced rank regression method. Sensitivity, specificity, positive predictive value, and negative predictive value were used to assess the performance of DDI in evaluating depression in the validation dataset (n = 1176).Results: Receiver operating characteristic analysis was constructed to determine the best cut-off value of DDI in predicting depression. In the study population, the DDI ranged from -3.126 to 1.810. The discriminative ability of DDI in predicting depression was good with the AUC of 0.799 overall, 0.794 in males and 0.808 in females. The best cut-off values of DDI for depression prediction were 0.204 overall, 0.330 in males and 0.034 in females. DDI was a validated method to assess the effects of diet on depression.Conclusion: Among individual food components in DDI, fermented vegetables, fresh vegetables, whole grains and onions were inversely associated, whereas legumes, pickled vegetables and rice were positively associated with depressive symptoms.

Association of a dietary pattern related to serum vitamin D levels with metabolic syndrome risk among Korean adults: based on the Korean national health and nutrition examination survey.

PURPOSE: Vitamin D has a crucial role in our metabolic health. We aimed to examine associations of vitamin D status and its related dietary pattern (DP) with prevalent risk of metabolic syndrome (MetS) in 9,237 Korean adults aged 19-64 years based on the National Health and Nutrition Examination Survey. METHODS: Vitamin D status was examined by serum 25-hydroxyvitamin D (25(OH)D). A vitamin D-related DP associated with 25(OH)D levels was derived using reduced rank regression (RRR). Associations of vitamin D status and its related DP with MetS prevalence were examined using multivariable logistic regression models adjusted for potential confounders. RESULTS: Men with sufficient vitamin D status had a 44% lower risk of MetS prevalence (OR: 0.56; 95%CI: 0.36-0.87) compared to those with deficiency. A vitamin D-related DP derived using RRR was characterized by high intakes of vegetables, fish, fruits, and nuts and low intakes of eggs, oils, and mushrooms in this study population. Among men, the DP was significantly associated with a lower risk of MetS prevalence, showing a 12% (95%CI: 4-20%) reduction in risk for a one-unit increase in the DP score. However, there was no significant association among women. CONCLUSION: The study's findings suggest that a sufficient vitamin D status and a related DP with high intakes of vegetables, fish, fruit, and nuts were associated with the risk of MetS, particularly in Korean male adults.

Difference in Gastrointestinal Cancer Risk and Mortality by Dietary Pattern Analysis: A Systematic Review and Meta-Analysis.

CONTEXT: Several studies have demonstrated that dietary patterns identified by a posteriori and hybrid methods are associated with gastrointestinal (GI) cancer risk and mortality. These studies applied different methods for analyzing dietary data and reported inconsistent findings. OBJECTIVE: This systematic review and meta-analysis were aimed to determine the association between dietary patterns, derived using principal component analysis (PCA) and reduced rank regression (RRR), and GI cancer risk and GI cancer-caused mortality. DATA SOURCE: Articles published up to June 2023 in English were eligible for inclusion. The Medline, SCOPUS, Cochrane Library, CINHAL, PsycINFO, ProQuest, and Web of Sciences databases were used to identify prospective studies. The Preferred Reporting Item for Systematic Review and Meta-analysis Protocol 2020 was used to report results. DATA EXTRACTION: A total of 28 studies were eligible for inclusion. Varied approaches to deriving dietary patterns were used, including PCA (n = 22), RRR (n = 2), combined PCA and RRR (n = 1), cluster analysis (CA; n = 2) and combined PCA and CA (n = 1). DATA ANALYSIS: Two dietary patterns, "healthy" and "unhealthy," were derived using PCA and RRR. The healthy dietary pattern was characterized by a higher intake of fruits, whole grains, legumes, vegetables, milk, and other dairy products, whereas the unhealthy dietary pattern was characterized by a higher intake of red and processed meat, alcohol, and both refined and sugar-sweetened beverages. The findings indicated that the PCA-derived healthy dietary pattern was associated with an 8% reduced risk (relative risk [RR], 0.92; 95% CI, 0.87-0.98), and the unhealthy dietary pattern was associated with a 14% increased risk (RR, 1.14; 95% CI, 1.07-1.22) of GI cancers. Similarly, the RRR-derived healthy dietary pattern (RR, 0.83; 95% CI, 0.61-1.12) may be associated with reduced risk of GI cancers. In contrast, the RRR-derived unhealthy dietary pattern (RR, 0.93; 95% CI, 0.57-1.52) had no association with a reduced risk of GI cancers. Similarly, evidence suggested that PCA-derived healthy dietary patterns may reduce the risk of death from GI cancers, whereas PCA-derived unhealthy dietary patterns may increase the risk. CONCLUSION: Findings from prospective studies on the association of PCA-derived dietary patterns and the risk of GI cancers support the evidence of healthy and unhealthy dietary patterns as either protective or risk-increasing factors for GI cancers and for survivorship, respectively. The findings also suggest that the RRR-derived healthy dietary pattern reduces the risk of GI cancers (albeit with low precision), but no association was found for the RRR-derived unhealthy dietary pattern. Prospective studies are required to further clarify disparities in the association between PCA- and RRR-derived dietary patterns and the risk of GI cancers. Systematic review registration: PROSPERO registration no. CRD42022321644.

Dietary patterns and the risk of diabetes in Korean adults: A cross-sectional and prospective cohort study.

OBJECTIVE: The aim of this study was to identify dietary patterns associated with diabetes in Korean adults and to investigate their association with diabetes risk in both a cross-sectional and prospective study. METHODS: Predefined food groups collected by the Korea National Health and Nutrition Examination Survey (KNHANES 2015-2018, n = 19 721) were entered in a reduced rank regression (RRR) model, followed by stepwise linear regression analyses to identify the most predictive dietary patterns. We evaluated the construct validity of dietary patterns in two independent samples from KNHANES 2019 to 2021 (n = 14 223) and the Health Examinees (HEXA) cohort study (n = 30 013). Associations between dietary patterns and diabetes risk were examined using multivariable regression and multivariable-adjusted Cox proportional hazard models, respectively. RESULTS: A dietary pattern was identified with high positive loadings for refined white rice, kimchi and salted vegetables, wheat flour and bread, and seasonings, and high negative loadings for whole grains, legumes with tofu and soymilk, poultry, eggs, and plant oils. The higher pattern scores were significantly associated with diabetes risk in KNHANES 2015 to 2018 (male: odds ratio [OR]: 1.59; 95% confidence interval [CI]: 1.35, 1.88; female: OR: 1.37; 95% CI: 1.18, 1.52), KNHANES 2019 to 2021 (male: OR: 1.47; 95% CI: 1.01, 1.69; female: OR: 1.37; 95% CI: 1.18, 1.54), and HEXA study (male: hazard ratio [HR]: 1.10; 95% CI: 1.01, 1.34; female: HR: 1.24; 95% CI: 1.02, 1.52). CONCLUSIONS: Dietary patterns derived by RRR followed by stepwise linear regression analyses were associated with increased risks of diabetes among Korean adults.

Associations Between Dietary Patterns and Kidney Health Assessed in the Population-Based CHRIS Study Using Reduced Rank Regression.

OBJECTIVE: While diet plays a key role in chronic kidney disease (CKD) management, the potential for diet to impact CKD prevention in the general population is less clear. Using a priori knowledge, we derived disease-related dietary patterns (DPs) through reduced rank regression (RRR) and investigated associations with kidney function, separately focusing on generally healthy individuals and those with self-reported kidney diseases, hypertension, or diabetes mellitus. METHODS: Eight thousand six hundred eighty-six participants from the population-based Cooperative Health Research in South Tyrol study were split into a group free of kidney disease, hypertension and diabetes (n = 6,133) and a group with any of the 3 conditions (n = 2,553). Diet was assessed through the self-administered Global Allergy and Asthma Network of Excellence food frequency questionnaire and DPs were derived through RRR selecting food frequency questionnaire-derived sodium, potassium, phosphorus, and protein intake as mediators. Outcomes were creatinine-based estimated glomerular filtration rate, urinary albumin-to-creatinine ratio, CKD and microalbuminuria. Multiple linear and logistic models were used to assess associations between RRR-based DPs and kidney outcomes separately in the 2 analytic groups. RESULTS: We identified 3 DPs, where high adherence reflected high levels of all nutrients (DP1), high potassium-phosphorus and low protein-sodium levels (DP2), and low potassium-sodium and high protein-phosphorus levels (DP3), respectively. We observed heterogeneous associations with kidney outcomes, varying by analytic group and sex. Kidney outcomes were much more strongly associated with DPs than with single nutrients. CONCLUSION: RRR is a feasible approach to estimate disease-related DPs and explore the combined effects of nutrients on kidney health. Heterogeneous associations across kidney outcomes suggest possible specificity to kidney function or damage. In individuals reporting kidney disease, hypertension or diabetes, specific dietary habits were associated with better kidney health, indicating that disease-specific dietary interventions can be effective for disease control.

Trimethylamine N-oxide, ß-alanine, tryptophan index, and vitamin B6-related dietary patterns in association with stroke risk.

BACKGROUND AND AIMS: The aim of this study was to examine the associations of dietary patterns derived by reduced-rank regression (RRR) model reflecting variation in novel biomarkers (trimethylamine N-oxide, ß-alanine, tryptophan index, and vitamin B6) with stroke risk. METHODS AND RESULTS: We performed analyses based on a community-based cohort study "the Prospective Follow-up Study on Cardiovascular Morbidity and Mortality in China (PFS-CMMC)". Factor loadings were calculated by RRR using 11 food groups collected via a validated food frequency questionnaire and the four response variables based on its nested case-control data (393 cases of stroke vs. 393 matched controls). Dietary pattern scores were derived by applying the factor loadings to the food groups in the entire cohort (n = 15,518). The associations of dietary pattern with the stroke risk were assessed using Cox proportional hazards models. The dietary pattern characterized with higher intakes of red meat and poultry but lower intakes of fresh vegetables, fresh fruits, and fish/seafoods were identified for further analyses. The hazard ratios (HR) for the highest vs. lowest quartile was 1.55 [95 % confidence interval (CI): 1.18-2.03, P trend = 0.001] for total stroke, 2.96 [95 % CI: 1.53-5.71, P trend <0.001] for non-ischemic stroke, after adjustment for sex, age, educational attainment, current smoking, current drinking, body mass index, total energy intake, family history of stroke, hypertension, diabetes, hyperlipidemia, and estimated glomerular filtration rate. CONCLUSION: Our findings highlight the importance of limited meat intake and increased intakes of fresh vegetables, fruits, and fish/seafoods in the prevention of stroke among Chinese adults.

Dietary patterns derived by reduced rank regression are associated with lipid disorders among Korean adults: a cross-sectional analysis.

BACKGROUND: Lipid disorders are a potent risk factor for cardiovascular diseases. Moreover, the intake of dietary fatty acids has been closely related to blood lipid levels. Therefore, this cross-sectional study examined the associations between dietary patterns related to fatty acid intake and lipid disorders in Korean adults. METHODS: From the 2013-2019 Korea National Health and Nutrition Examination Surveys data, 8399 men and 11404 women (aged ≥ 19 years) were selected. Reduced rank regression was employed to identify dietary patterns from 26 food groups, aiming to explain the maximum variation in the intake of saturated fatty acids (SFA), polyunsaturated fatty acids (PUFA), omega-3 fatty acids, and the PUFA/SFA ratio. Associations of quintiles (Q) of dietary pattern scores with lipid disorders were examined using multiple logistic regression stratified by sex. RESULTS: Three dietary patterns were identified: dietary pattern 1 showed positive factor loadings for vegetable oils, seasonings, legumes, nuts, and fish; dietary pattern 2 was high in consumption of red meat, bread and snacks, and milk and dairy products; and dietary pattern 3 was rich in fish and milk and dairy products. In men, dietary pattern 3 was inversely associated with elevated triglycerides (Q5 vs. Q1: odds ratio [OR] = 0.82, 95% confidence interval [CI] = 0.69-0.97, P-trend = 0.008). In women, dietary pattern 2 was positively associated with elevated total cholesterol (OR = 1.31, 95% CI = 1.12-1.52, P-trend < 0.001) but inversely associated with low HDL-cholesterol (OR = 0.70, 95% CI = 0.59-0.83, P-trend < 0.001). CONCLUSION: In this study, dietary patterns explaining the intake of various types of fatty acids were differentially associated with lipid disorders in Korean adults. Dietary pattern characterized by higher intakes of red meat, bread and snacks and milk and dairy products were positively associated with elevated total cholesterol, whereas dietary pattern rich in fish consumption showed an inverse association with elevated triglycerides. These findings could be instrumental in developing dietary guidelines and strategies for preventing and managing lipid disorders in this population.

Multiple augmented reduced rank regression for pan-cancer analysis.

Statistical approaches that successfully combine multiple datasets are more powerful, efficient, and scientifically informative than separate analyses. To address variation architectures correctly and comprehensively for high-dimensional data across multiple sample sets (ie, cohorts), we propose multiple augmented reduced rank regression (maRRR), a flexible matrix regression and factorization method to concurrently learn both covariate-driven and auxiliary structured variations. We consider a structured nuclear norm objective that is motivated by random matrix theory, in which the regression or factorization terms may be shared or specific to any number of cohorts. Our framework subsumes several existing methods, such as reduced rank regression and unsupervised multimatrix factorization approaches, and includes a promising novel approach to regression and factorization of a single dataset (aRRR) as a special case. Simulations demonstrate substantial gains in power from combining multiple datasets, and from parsimoniously accounting for all structured variations. We apply maRRR to gene expression data from multiple cancer types (ie, pan-cancer) from The Cancer Genome Atlas, with somatic mutations as covariates. The method performs well with respect to prediction and imputation of held-out data, and provides new insights into mutation-driven and auxiliary variations that are shared or specific to certain cancer types.

Association of the Protective Dietary Pattern for Blood Pressure with Elevated Blood Pressure and Hypertension among Chinese Children and Adolescents Aged 6-17 Years Old: Data from China Nutrition and Health Surveillance (2015-2017).

Studies focused on the association between dietary patterns and elevated blood pressure (BP) and hypertension (HTN) among children and adolescents remain insufficient. This study aimed to explore a dietary pattern that could be helpful for the prevention of abnormal BP and to investigate the association between this dietary pattern and elevated BP and HTN among Chinese children and adolescents. A total of 52,080 Chinese children and adolescents aged 6~17 years old from the China Nutrition and Health Surveillance (CNHS) 2015-2017 were included in the current study. The reduced rank regression (RRR) method was applied to derive a dietary pattern that is associated with BP. Multivariable logistic regression was used to assess the association between dietary pattern (DP) and elevated BP and HTN. The Dietary Approach to Stop Hypertension (DASH) score was also calculated for each participant as a comparative method to validate the dietary pattern derived with the RRR method. A protective dietary pattern (PDP) for BP among Chinese children and adolescents was derived, which was characterized by high intakes of dairy products, mushrooms/edible fungi, fresh vegetables, fresh fruits, fresh eggs, aquatic products, mixed legumes, soybeans and related products, offal, dried fruits, and coarse cereals, with low intakes of refined grains. After multiple adjustments, there were significant inverse associations between PDP scores and the odds of elevated BP and HTN (elevated BP: Q5 vs. Q1, OR = 0.849, 95%CI = 0.755-0.931, P-trend < 0.05; HTN: Q5 vs. Q1, OR = 0.795, 95%CI = 0.694-0.911, P-trend < 0.05). The DASH diet was also observed to have protective effects on elevated BP in model I (Q5 vs. Q1, OR = 0.899, 95%CI = 0.828-0.975, P-trend < 0.05), but was not observed to have protective effects on HTN (HTN: Q5 vs. Q1, OR = 0.958, 95%CI = 0.876-1.048, P-trend > 0.05). The current study suggested that greater adherence to the PDP for BP among Chinese children and adolescents might be associated with lower odds of elevated BP and HTN.

Cholesterol-rich dietary pattern during early pregnancy and genetic variations of cholesterol metabolism genes in predicting gestational diabetes mellitus: a nested case-control study.

BACKGROUND: Higher dietary cholesterol intake during pregnancy increases risk of gestational diabetes mellitus (GDM). However, no studies have investigated interindividual variability in cholesterol metabolism and the association of genetics and diet on GDM. OBJECTIVE: ; To prospectively evaluate the joint association of cholesterol-rich dietary patterns and polymorphisms of genes coding for cholesterol metabolism pathway proteins with GDM. METHODS: A total of 1116 pregnant females from the Tongji Birth Cohort were enrolled. GDM was diagnosed according to a 75-g 2-h oral glucose tolerance test at 24-28 wk of gestation. Dietary data were collected by a validated food frequency questionnaire. The reduced-rank regression method was used to identify dietary patterns using dietary cholesterol as the response variable. Time-of-flight mass spectrometry was used for genotyping. The genetic risk score (GRS) for GDM was constructed with genetic variants in 28 cholesterol metabolism-related single-nucleotide polymorphisms (SNPs). Conditional logistic regression models were used to assess the odds ratio (OR) for GDM. RESULTS: The cholesterol-rich dietary pattern was rich in livestock and poultry meat and eggs but lower in cereals. The multivariable-adjusted ORs for GDM were 1.24 (95% confidence interval: 1.06-1.44) per SD increment of cholesterol-rich pattern scores and 1.28 (1.09-1.49) per tertile GRS. The variants of the CYP7A1 rs3808607 G→T/rs8192871 G→A/rs7833904 A→T, as well as AGGG and TTGA haplotypes of 4 CYP7A1-spanning SNPs, were significantly associated with GDM. For the joint effect, the OR was 3.53 (1.71-7.31) in the highest categories of both dietary pattern scores and GRS compared with individuals with the lowest strata without significant interaction (P for interaction = 0.101). CONCLUSIONS: Both a cholesterol-rich dietary pattern and genetic variants of cholesterol metabolism genes are associated with risk of GDM. Adherence to a cholesterol-rich dietary pattern during early pregnancy promotes the chance of GDM, especially in women with higher GRS. CLINICAL TRIAL REGISTRY: This trial was registered at http://www.chictr.org.cn (Registration number: ChiCTR1800016908). URL: =https://www.chictr.org.cn/showprojEN.html?proj=28081.

Stability Approach to Regularization Selection for Reduced-Rank Regression.

The reduced-rank regression model is a popular model to deal with multivariate response and multiple predictors, and is widely used in biology, chemometrics, econometrics, engineering, and other fields. In the reduced-rank regression modelling, a central objective is to estimate the rank of the coefficient matrix that represents the number of effective latent factors in predicting the multivariate response. Although theoretical results such as rank estimation consistency have been established for various methods, in practice rank determination still relies on information criterion based methods such as AIC and BIC or subsampling based methods such as cross validation. Unfortunately, the theoretical properties of these practical methods are largely unknown. In this paper, we present a novel method called StARS-RRR that selects the tuning parameter and then estimates the rank of the coefficient matrix for reduced-rank regression based on the stability approach. We prove that StARS-RRR achieves rank estimation consistency, i.e., the rank estimated with the tuning parameter selected by StARS-RRR is consistent to the true rank. Through a simulation study, we show that StARS-RRR outperforms other tuning parameter selection methods including AIC, BIC, and cross validation as it provides the most accurate estimated rank. In addition, when applied to a breast cancer dataset, StARS-RRR discovers a reasonable number of genetic pathways that affect the DNA copy number variations and results in a smaller prediction error than the other methods with a random-splitting process.

The associations of dietary patterns with depressive and anxiety symptoms: a prospective study.

BACKGROUND: Diet is increasingly recognized as an important risk factor for mental health. However, evidence regarding the association between diet pattern and depressive and anxiety symptoms is limited. We aimed to investigate the associations of dietary patterns characterized by a set of nutrients of interest with depressive and anxiety symptoms. METHODS: The analyses included a total of 126,819 participants in the UK Biobank who had completed at least two dietary questionnaires. Dietary data were obtained through 24-h dietary assessment at baseline between 2006 and 2010 and four rounds of online follow-ups between 2011 and 2012. Reduced rank regression was applied to derive dietary patterns (DPs) explaining variability in energy density, free sugars, saturated fat, and fiber intakes. Depressive and anxiety symptoms were measured by the Patient Health Questionnaire-9 and General Anxiety Disorder-7 between 2016 and 2017, respectively. Logistic regression models were performed to investigate the associations between dietary patterns and depressive and anxiety symptoms. RESULTS: During a mean follow-up of 7.6 years, 2746 cases of depressive symptoms and 2202 cases of anxiety symptoms were recorded. Three major DPs were derived, explaining 74% of the variation in nutrients hypothesized to be related to depressive and anxiety symptoms. DP1 was characterized by high intakes of chocolate, confectionery, butter, and low vegetable/fruit intakes. Compared to the lowest quintile of DP1, the odds ratio (95% confidence interval) of depressive symptoms for Q2-Q5 was 0.82 (0.72-0.93), 0.86 (0.76-0.98), 1.02 (0.90-1.15), and 1.17 (1.03-1.32), respectively. Compared to the lowest quintile of DP1, the odds ratio (95% CI) of anxiety symptoms for Q2-Q5 was 0.84 (0.73-0.97), 0.91 (0.79-1.05), 1.01 (0.88-1.15), and 1.18 (1.03-1.35), respectively. DP2 featured high intakes of sugar-sweetened beverages, added sugars, and low intakes of butter/cheese but showed no significant links to depressive or anxiety symptoms. DP3 was characterized by high butter and milk desserts and low alcohol/bread intakes. Compared to the lowest quintile of DP3, the odds ratio (95% CI) of depressive symptoms for Q2-Q5 was 0.90 (0.79-1.01), 1.00 (0.88-1.13), 1.06 (0.94-1.20), and 1.17 (1.03-1.32), respectively. Compared to the lowest quintile of DP3, the odds ratio (95% CI) of anxiety symptoms for Q2-Q5 was 0.90 (0.78-1.04), 1.05 (0.91-1.20), 1.02 (0.89-1.17), and 1.21 (1.05-1.38), respectively. CONCLUSIONS: A DP characterized by high intakes of chocolate and confectionery, butter, high-fat cheese, added sugars, along with low intakes of fresh fruit and vegetables, is associated with a higher risk of depressive and anxiety symptoms.

Nutrient intakes from complementary foods are associated with cardiometabolic biomarkers among undernourished Peruvian children.

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.

Associations between an obesity-related dietary pattern and incidence of overall and site-specific cancers: a prospective cohort study.

BACKGROUND: A dietary pattern (DP) may impact on cancer incidence more strongly than individual foods, but this association remains uncertain. Here, we aimed to broadly explore the associations of an obesity-related DP with overall and 19 site-specific cancers. METHODS: This study included 114,289 cancer-free participants with at least two dietary assessments. A total of 210 food items were classified into 47 food groups, and the mean amount of each food group was used in reduced-rank regression to derive the obesity-related DP. Cox regressions were conducted to explore the associations of the obesity-related DP with overall and 19 site-specific cancers. The parallel mediation model was constructed to quantify the mediating roles of potential mediators. RESULTS: During a median follow-up period of 9.4 years, 10,145 (8.9%) incident cancer cases were documented. The derived-DP was characterized by a higher intake of beer and cider, processed meat, high sugar beverages, red meat, and artificial sweetener, and a lower intake of fresh vegetables, olive oil, tea, and high fiber breakfast cereals. Observational analysis showed that a higher obesity-related DP Z-score was linearly associated with an increased risk of overall cancer (adjusted hazard ratio (HR) = 1.02, 95% CI: 1.01, 1.04 per 1-SD increase, corrected P < 0.001). For site-specific cancer, positive linear associations for six cancer sites (oral, colorectal, liver, lung, endometrium, and thyroid) and nonlinear associations for six cancer sites (esophagus, malignant melanoma, prostate, kidney, bladder, and multiple myeloma) were observed. The paralleled mediation analysis suggested that the association between the obesity-related DP and overall cancer is mediated by the body mass index (BMI), the waist-to-hip ratio (WHR), C-reactive protein, high-density lipoproteins (HDLs), and triglycerides. CONCLUSIONS: The developed obesity-related DP is strongly associated with overall and multiple cancer sites. Our findings highlight the complicated and diverse associations between an obesity-related DP and cancers and provide clues for future research directions.

Latent neural dynamics encode temporal context in speech.

Direct neural recordings from human auditory cortex have demonstrated encoding for acoustic-phonetic features of consonants and vowels. Neural responses also encode distinct acoustic amplitude cues related to timing, such as those that occur at the onset of a sentence after a silent period or the onset of the vowel in each syllable. Here, we used a group reduced rank regression model to show that distributed cortical responses support a low-dimensional latent state representation of temporal context in speech. The timing cues each capture more unique variance than all other phonetic features and exhibit rotational or cyclical dynamics in latent space from activity that is widespread over the superior temporal gyrus. We propose that these spatially distributed timing signals could serve to provide temporal context for, and possibly bind across time, the concurrent processing of individual phonetic features, to compose higher-order phonological (e.g. word-level) representations.

Novel approach to investigate the association between type 2 diabetes risk and dietary fats in a dietary pattern context: a scoping review.

The effect of dietary fat on type 2 diabetes (T2D) risk is unclear. A posteriori dietary pattern methods have been increasingly used to investigate how dietary fats impact T2D risk. However, the diverse nutrients, foods and dietary patterns reported in these studies requires examination to better understand the role of dietary fats. This scoping review aimed to systematically search and synthesize the literature regarding the association between dietary patterns characterized by dietary fats and T2D risk using reduced rank regression. Medline and Embase were searched for cross-sectional, cohort or case-control studies published in English. Of the included studies (n = 8), five high-fat dietary patterns, mostly high in SFA, were associated with higher T2D risk or fasting glucose, insulin and Homeostasis Model Assessment (HOMA) levels. These were mostly low-fiber (n = 5) and high energy-density (n = 3) dietary patterns characterized by low fruit and vegetables intake, reduced fat dairy products and higher processed meats and butter intake. Findings from this review suggest that a posteriori dietary patterns high in SFA that increase T2D risk are often accompanied by lower fruits, vegetables and other fiber-rich foods intake. Therefore, healthy dietary fats consumption for T2D prevention should be encouraged as part of a healthful dietary pattern.

Association of maternal dietary patterns derived by multiple approaches with gestational diabetes mellitus: a prospective cohort study.

We used two a priori diet scores [Mediterranean diet (aMed) and Diet Balance Index (DBI)] and two a posteriori approaches [principal components analysis (PCA) and reduced-rank regression (RRR)] to examine the association of maternal dietary patterns with risk of gestational diabetes mellitus (GDM) and blood glucose among 2202 pregnant women in the Tongji Birth Cohort. Compared to the highest quartile of the aMed and legumes-vegetables-fruits (derived by PCA) scores, the fasting blood glucose (FBG) levels were higher in the lower quartiles (p-trend < 0.05). Lower scores of the meats-eggs-dairy (derived by PCA) and eggs-fish patterns (derived by RRR; characterised by higher intakes of freshwater fish, eggs, and lower intakes of leafy and cruciferous vegetables and fruits) were associated with decreased FBG levels (p-trend < 0.05). Similarities were found across approaches that some dietary patterns were associated with FBG, but not with postprandial glucose and GDM risk.

Comparison of data-driven identified hypertension-protective dietary patterns among Chinese adults: based on a nationwide study.

PURPOSE: Diet pattern (DP) is a key modifiable and cost-effective factor in hypertension (HTN) management. The current study aimed to identify and compare the hypertension-protective DPs among Chinese adults. METHODS: 52,648 participants aged over 18 years were included from China Nutrition and Health Surveillance (CNHS) 2015-2017. Reduced rank regression (RRR) and partial least square regression (PLS) was applied to identify the DPs. Multivariable-adjusted logistic regression was used to assess the association between the DPs and HTN. RESULTS: DPs derived by RRR and PLS were both featured by higher consumption of fresh vegetables and fruits, mushrooms and edible fungi, seaweeds, soybeans and related products, mixed legumes, dairy products, fresh eggs, and lower of refined grain consumption. Compared to the lowest quintile, participants in the highest quintile had lower odds of HTN (RRR-DP: OR = 0.77, 95% CI = 0.72-0.83; PLS-DP: OR = 0.76, 95% CI = 0.71-0.82; all p < 0.0001). Simplified DP scores were observed the same protective tendencies (Simplified RRR-DP: OR = 0.81, 95% CI = 0.75-0.87; Simplified PLS-DP: OR = 0.79, 95% CI = 0.74-0.85; all p < 0.0001) and showed effective extrapolation in subgroups defined by gender, age, location, lifestyle, and different metabolic conditions. CONCLUSIONS: The identified DPs had high conformity with East Asian dietary habits, and significantly negative associations with HTN among Chinese adults. The simplified DP technique also indicated the potential for improving the extrapolation of the results of DP analysis related to HTN.

Bayesian predictive modeling of multi-source multi-way data.

A Bayesian approach to predict a continuous or binary outcome from data that are collected from multiple sources with a multi-way (i.e., multidimensional tensor) structure is described. As a motivating example, molecular data from multiple 'omics sources, each measured over multiple developmental time points, as predictors of early-life iron deficiency (ID) in a rhesus monkey model are considered. The method uses a linear model with a low-rank structure on the coefficients to capture multi-way dependence and model the variance of the coefficients separately across each source to infer their relative contributions. Conjugate priors facilitate an efficient Gibbs sampling algorithm for posterior inference, assuming a continuous outcome with normal errors or a binary outcome with a probit link. Simulations demonstrate that the model performs as expected in terms of misclassification rates and correlation of estimated coefficients with true coefficients, with large gains in performance by incorporating multi-way structure and modest gains when accounting for differing signal sizes across the different sources. Moreover, it provides robust classification of ID monkeys for the motivating application.