Associations between explorative dietary patterns and serum lipid levels and their interactions with ApoA5 and ApoE haplotype in patients with recently diagnosed type 2 diabetes

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.

Prediction of potential drug-microbe associations based on matrix factorization and a three-layer heterogeneous network

Microbes in the human body are closely linked to many complex human diseases and are emerging as new drug targets. These microbes play a crucial role in drug development and disease treatment. Traditional methods of biological experiments are not only time-consuming but also costly. Using computational methods to predict microbe-drug associations can effectively complement biological experiments. In this experiment, we constructed heterogeneity networks for drugs, microbes, and diseases using multiple biomedical data sources. Then, we developed a model with matrix factorization and a three-layer heterogeneous network (MFTLHNMDA) to predict potential drug-microbe associations. The probability of microbe-drug association was obtained by a global network-based update algorithm. Finally, the performance of MFTLHNMDA was evaluated in the framework of leave-one-out cross-validation (LOOCV) and 5-fold cross-validation (5-fold CV). The results showed that our model performed better than six state-of-the-art methods that had AUC of 0.9396 and 0.9385 + /- 0.0000, respectively. This case study further confirms the effectiveness of MFTLHNMDA in identifying potential drug-microbe associations and new drug-microbe associations.

Apolipoprotein A5 gene polymorphism (rs662799) and cardiovascular disease in end-stage kidney disease patients

Background

Plasma triglyceride (TG) levels are a significant risk factor for cardiovascular disease (CVD). The APOA5 gene is one of the crucial factors in plasma TG metabolism regulation. The rs662799 polymorphism in the APOA5 gene has been reported to be associated with cardiovascular disease. The goal of this study was to evaluate the potential association of this variant with CVD in patients with end-stage kidney disease. 

Methods

In this case–control study the polymorphism was analyzed using the PCR–RFLP method in 800 consecutive patients with ESKD and 500 healthy controls. The genotype and allele distribution was compared between subgroups of patients with CVD (552) versus those without CVD (248).

Results

The frequency of the minor allele (C) in the healthy individuals was 9% compared to 12% in ESRD group (p = 0.09). The difference between groups was slightly higher for CC homozygote (3.5% versus 1.6%, p = 0.042). The ESKD patient group was analyzed according to the presence or absence of CVD. The significant differences in the polymorphism distribution were revealed in this analysis. The frequency of the C allele in the CVD + subgroup was 14% compared to 6% in CVD- patients (p = 0.001). In the CVD + subgroup the ORs (95% CI) for the C allele and CC genotype were 2.41 (1.61–3.6), p < 0.001 and 3.13 (1.07–9.14), p = 0.036, respectively. This indicates to the association of the variant C allele with cardiovascular disease in ESKD patients. The CC homozygotes have a threefold higher odds of CVD compared to TT homozygotes. The highest frequency of the C allele (18%) was observed in subgroup of patients with diabetic nephropathy, with OR (95% CI) 3.40 (2.13–5.43), p < 0.001.The presence of minor allele (CC and CT genotypes) was significantly associated with increased plasma triglyceride levels (p < 0.001 for both CVD + and CVD- groups).

Conclusion

The present study demonstrated the effect of rs662799 polymorphism on plasma TG levels and its association with the development of cardiovascular disease in ESKD patients.

Using Multiple Statistical Methods to Derive Dietary Patterns Associated with Cardiovascular Disease in Patients with Type 2 Diabetes: Results from a Multiethnic Population-Based Study

Background

There are few reports on the relationship between dietary patterns and cardiovascular disease (CVD) risk in patients with type 2 diabetes (T2D). This study aimed to explore relationships between dietary patterns and CVD risk in the T2D population using multiple statistical analysis methods.

Methods

A total of 2,984 patients with T2D from the Xinjiang Multi-Ethnic Cohort, 555 of whom were suffering from CVD, were enrolled in this study. Participants' dietary intake was measured by the semiquantitative food frequency questionnaire (FFQ). Three statistical methods were used to construct dietary patterns, including principal component analysis (PCA) method, reduced-rank regressions (RRR) method, and partial least-squares regression (PLS) method. Then, the association between dietary patterns and CVD risk in T2D patients was analyzed by logistic regression. After excluding participants with CVD, the associations between dietary patterns and 10-year CVD risk scores were subsequently evaluated to reduce reverse causality.

Results

In this study, four dietary patterns were identified by three methods. Adjustment for confounding factors, subjects with the highest scores on the "high-protein and high-carbohydrate" patterns derived from PCA, RRR, and PLS had higher odds of CVD than those with the lowest scores (OR: 2.89, 95% CI: 2.11-3.96, P _trend < 0.001; OR: 2.96, 95% CI: 2.17-4.03, P _trend < 0.001; OR: 2.01, 95% CI: 1.50-2.70, P _trend < 0.001, respectively). However, the dietary pattern of PCA-prudent was not significantly related to the odds of having CVD in T2D patients (adjusted OR_Q4vsQ1: 0.93, 95% CI: 0.70-1.24, P _trend =0.474). Interestingly, we also found significant associations between "high-protein and high-carbohydrate" patterns and the elevated predicted 10-year CVD risk in T2D patients (all P _trend < 0.05).

Conclusion

The positive correlation between "high-protein and high-carbohydrate" patterns and CVD risk in T2D patients was robust across all three data-driven approaches. These findings may have public health significance, encouraging an emphasis on food choices in the usual diet and promoting nutritional interventions for patients with T2D to prevent CVD.

Identification of candidate biomarkers and pathways associated with type 1 diabetes mellitus using bioinformatics analysis

Type 1 diabetes mellitus (T1DM) is a metabolic disorder for which the underlying molecular mechanisms remain largely unclear. This investigation aimed to elucidate essential candidate genes and pathways in T1DM by integrated bioinformatics analysis. In this study, differentially expressed genes (DEGs) were analyzed using DESeq2 of R package from GSE162689 of the Gene Expression Omnibus (GEO). Gene ontology (GO) enrichment analysis, REACTOME pathway enrichment analysis, and construction and analysis of protein–protein interaction (PPI) network, modules, miRNA-hub gene regulatory network and TF-hub gene regulatory network, and validation of hub genes were performed. A total of 952 DEGs (477 up regulated and 475 down regulated genes) were identified in T1DM. GO and REACTOME enrichment result results showed that DEGs mainly enriched in multicellular organism development, detection of stimulus, diseases of signal transduction by growth factor receptors and second messengers, and olfactory signaling pathway. The top hub genes such as MYC, EGFR, LNX1, YBX1, HSP90AA1, ESR1, FN1, TK1, ANLN and SMAD9 were screened out as the critical genes among the DEGs from the PPI network, modules, miRNA-hub gene regulatory network and TF-hub gene regulatory network. Receiver operating characteristic curve (ROC) analysis confirmed that these genes were significantly associated with T1DM. In conclusion, the identified DEGs, particularly the hub genes, strengthen the understanding of the advancement and progression of T1DM, and certain genes might be used as candidate target molecules to diagnose, monitor and treat T1DM.

Graph2MDA: a multi-modal variational graph embedding model for predicting microbe-drug associations

MOTIVATION

Accumulated clinical studies show that microbes living in humans interact closely with human hosts, and get involved in modulating drug efficacy and drug toxicity. Microbes have become novel targets for the development of antibacterial agents. Therefore, screening of microbe-drug associations can benefit greatly drug research and development. With the increase of microbial genomic and pharmacological datasets, we are greatly motivated to develop an effective computational method to identify new microbe-drug associations.

RESULTS

In this article, we proposed a novel method, Graph2MDA, to predict microbe-drug associations by using variational graph autoencoder (VGAE). We constructed multi-modal attributed graphs based on multiple features of microbes and drugs, such as molecular structures, microbe genetic sequences and function annotations. Taking as input the multi-modal attribute graphs, VGAE was trained to learn the informative and interpretable latent representations of each node and the whole graph, and then a deep neural network classifier was used to predict microbe-drug associations. The hyperparameter analysis and model ablation studies showed the sensitivity and robustness of our model. We evaluated our method on three independent datasets and the experimental results showed that our proposed method outperformed six existing state-of-the-art methods. We also explored the meaning of the learned latent representations of drugs and found that the drugs show obvious clustering patterns that are significantly consistent with drug ATC classification. Moreover, we conducted case studies on two microbes and two drugs and found 75-95% predicted associations have been reported in PubMed literature. Our extensive performance evaluations validated the effectiveness of our proposed method.

AVAILABILITY AND IMPLEMENTATION

Source codes and preprocessed data are available at https://github.com/moen-hyb/Graph2MDA.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Plasma boron concentrations in the general population: a cross-sectional analysis of cardio-metabolic and dietary correlates

Purpose

Experimental evidence suggests positive effects of boron on health and metabolism, but human data are still scarce. We aimed to identify dietary and cardio-metabolic correlates of plasma boron concentrations in the general population.

Methods

In a community-based sample (n = 899, 57% men, mean age 61 years), plasma boron (median [IQR]: 33.80 µg/L [25.61; 44.65]) concentrations were measured by inductively coupled plasma-mass spectrometry. Overall (PDI), healthy (hPDI), and unhealthy (uPDI) plant-based diet indices were derived from a validated food frequency questionnaire. Reduced rank regression (RRR) yielded a dietary pattern explaining 30% of the variation of circulating boron. Cross-sectional associations of dietary indices and cardio-metabolic traits with plasma boron concentrations were assessed using multivariable-adjusted linear regression analysis.

Results

The RRR pattern was characterized by high intake of fruits, nuts/seeds, tea, wine and low intake of e.g. bread, poultry, processed meat, chocolate/sweets, and soft drinks. 10-point increments in PDI, hPDI, and uPDI were associated with 8.7% (95% CI: 4.2; 13.4), 10.4% (95% CI: 6.6; 14.3), and −8.8% (95% CI: −12.1; −5.4) change in plasma boron concentrations, respectively. Age and phosphate were directly, while BMI, plasma lipid concentrations, and CRP were inversely associated with circulating boron. Plasma boron concentrations were higher in summer vs. winter, in individuals taking vs. not taking antihypertensive medication, and in individuals with high or medium vs. low education level.

Conclusion

Higher plasma boron concentrations appeared to associate with a healthier diet, were related to lower BMI and a more favorable cardio-metabolic risk profile, and showed seasonal variations.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00394-021-02730-w.

Dietary Approaches to Stop Hypertension (DASH) diet, Mediterranean diet and blood lipid profiles in less-developed ethnic minority regions

Different from developed countries, there is a paucity of research examining how the Dietary Approaches to Stop Hypertension (DASH) and Mediterranean diets relate to lipids in less-developed ethnic minority regions (LEMR). A total of 83 081 participants from seven ethnic groups were retrieved from the baseline data of the China Multi-Ethnic Cohort study, which was conducted in less-developed Southwest China between May 2018 and September 2019. Multivariable linear regression models were then used to examine the associations of the DASH and alternative Mediterranean diet (AMED) scores, assessed by modified DASH score and AMED, as well as their components with total cholesterol (TC), LDL-cholesterol, HDL-cholesterol, TAG and TC/HDL-cholesterol. The DASH scores were negatively associated with TC, HDL-cholesterol and TAG. Comparing the highest quintiles with the lowest DASH scores, TC decreased 0·0708 (95 % CI -0·0923, -0·0493) mmol/l, HDL-cholesterol decreased 0·0380 (95 % CI -0·0462, -0·0299) mmol/l and TAG decreased 0·0668 (95 % CI -0·0994, -0·0341) mmol/l. The AMED scores were negatively associated with TC, LDL-cholesterol and HDL-cholesterol. Comparing the highest quintiles with the lowest AMED scores, TC decreased 0·0816 (95 % CI -0·1035, -0·0597) mmol/l, LDL-cholesterol decreased 0·0297 (95 % CI -0·0477, -0·0118) mmol/l and HDL-cholesterol decreased 0·0275 (95 % CI -0·0358, -0·0192) mmol/l. Although both the DASH diet and the Mediterranean diet were negatively associated with blood lipids, those associations showed different patterns in LEMR, particularly for TAG and HDL-cholesterol.

Apolipoprotein E Genotype, Meat, Fish, and Egg Intake in Relation to Mortality Among Older Adults: A Longitudinal Analysis in China

Introduction: The interactions between apolipoprotein E (APOE) genotype and diet pattern changes were found significant in several trials, implying that APOE gene may modify the effect of animal protein-rich food on health outcomes. We aim to study the interaction of APOE genotype with the effect of meat, fish and egg intake on mortality.

Methods: This population-based study enrolled 8,506 older adults (mean age: 81.7 years, 52.3% female) from the Chinese Longitudinal Healthy Longevity Study. The intake frequency of meat, fish and egg was assessed by 3-point questions at baseline. Cox regression was conducted to calculate the hazard ratios for all-cause mortality of intake levels of meat, fish and egg. The analyses were stratified by APOE genotype and sex. The analyses were performed in 2020.

Results: In the multivariable-adjusted models, meat and fish intake was associated with all-cause mortality (high vs. low intake: meat: HR: 1.14, 95% CI: 1.01, 1.28; fish: HR: 0.83, 95% CI: 0.73, 0.95). APOE genotype have significant interactions with meat and fish intake (Ps < 0.05). Compared with low fish intake, high fish intake was associated with lower risk of mortality (HR: 0.74, 95% CI: 0.56–0.98) only among the APOE ε4 carriers. High meat intake was significantly associated with higher risks of mortality (HR: 1.13, 95% CI: 1.04–1.25) only among the APOE ε4 non-carriers. The interactive relationship was restricted among the male. No significant findings were observed between egg and mortality among carriers or non-carriers.

Conclusions: Among Chinese older adults, the significance of associations of mortality with reported meat or fish intake depended on APOE-E4 carriage status. If validated by other studies, our findings provide evidence for gene-based “precision” lifestyle recommendations.

Interaction between APOE ε4 and dietary protein intake on cognitive decline: A longitudinal cohort study

OBJECTIVE

To exam the association of cognitive decline with APOE ε4 allele carriage and dietary protein intake and investigate whether there is a gene-diet (GxD) interaction of APOE ε4 allele carriage and dietary protein intake on cognitive decline in a nationwide cohort of older adults.

METHODS

A cohort study of participants from Chinese Longitudinal Healthy Longevity Survey was conducted from 2008 to 2014. A total of 3029 participants (mean age of 77.0 years, SD = 9.0; 49.3% were women) was enrolled. We genotyped APOE ε4 allele for each participant and calculated the diversity of dietary protein intake (DDPI) by summing up the frequency of intake of the 6 protein-rich foods (meats, fish, eggs, nuts, dairy products, and bean products). We assessed cognitive function using the Mini-Mental State Examination (MMSE). We used ordinal regression model to estimate the independent and joint effects of APOE ε4 carrier and dietary protein intake on cognitive decline, adjusting for potential confounders of age, sex, education, socio-economic status, lifestyles, BMI, and cardiometabolic conditions.

RESULTS

There was significant association between carrying APOE ε4 allele and faster cognitive decline (Odds ratio: 1.19, 95% CI = 1.00-1.42), independent of potential confounders. While the associations of DDPI and the intake of 6 protein-rich foods with cognitive decline did not reach any statistical significance. We observed significant interactions of APOE ε4 with DDPI and fish intake, at multiple correction-adjusted Ps < 0.05. In those who were APOE ε4 carriers rather than non-carriers, both high DDPI (OR = 0.54, 95% CI: 0.34-0.88) and daily fish intake (OR = 0.43, 95% CI: 0.22-0.78) were significantly associated with slower cognitive decline, respectively. We also found that frequent intake of fish benefits women more than men regarding the mitigating of cognitive decline among APOE ε4 allele carriers (P for interaction = 0.016).

CONCLUSIONS

The results of this study support the hypothesis that diversified protein food intake in addition to frequent fish intake may reduce the detrimental effect of APOE ε4 on cognitive health.

Common Genetic Variations Involved in the Inter-Individual Variability of Circulating Cholesterol Concentrations in Response to Diets: A Narrative Review of Recent Evidence

The number of nutrigenetic studies dedicated to the identification of single nucleotide polymorphisms (SNPs) modulating blood lipid profiles in response to dietary interventions has increased considerably over the last decade. However, the robustness of the evidence-based science supporting the area remains to be evaluated. The objective of this review was to present recent findings concerning the effects of interactions between SNPs in genes involved in cholesterol metabolism and transport, and dietary intakes or interventions on circulating cholesterol concentrations, which are causally involved in cardiovascular diseases and established biomarkers of cardiovascular health. We identified recent studies (2014-2020) that reported significant SNP-diet interactions in 14 cholesterol-related genes (NPC1L1, ABCA1, ABCG5, ABCG8, APOA1, APOA2, APOA5, APOB, APOE, CETP, CYP7A1, DHCR7, LPL, and LIPC), and which replicated associations observed in previous studies. Some studies have also shown that combinations of SNPs could explain a higher proportion of variability in response to dietary interventions. Although some findings still need replication, including in larger and more diverse study populations, there is good evidence that some SNPs are consistently associated with differing circulating cholesterol concentrations in response to dietary interventions. These results could help clinicians provide patients with more personalized dietary recommendations, in order to lower their risk for cardiovascular disease.

NDUFB6 Polymorphism Is Associated With Physical Activity-Mediated Metabolic Changes in Type 2 Diabetes

The rs540467 SNP in the NDUFB6 gene, encoding a mitochondrial complex I subunit, has been shown to modulate adaptations to exercise training. Interaction effects with diabetes mellitus remain unclear. We assessed associations of habitual physical activity (PA) levels with metabolic variables and examined a possible modifying effect of the rs540467 SNP. Volunteers with type 2 (n=242), type 1 diabetes (n=250) or normal glucose tolerance (control; n=139) were studied at diagnosis and subgroups with type 1 (n=96) and type 2 diabetes (n=95) after 5 years. Insulin sensitivity was measured by hyperinsulinemic-euglycemic clamps, oxygen uptake at the ventilator threshold (VO₂AT) by spiroergometry and PA by questionnaires. Translational studies investigated insulin signaling and mitochondrial function in Ndufb6 siRNA-treated C2C12 myotubes, with electronic pulse stimulation (EPS) to simulate exercising. PA levels were 10 and 6%, VO₂AT was 31% and 8% lower in type 2 and type 1 diabetes compared to control. Within 5 years, 36% of people with type 2 diabetes did not improve their insulin sensitivity despite increasing PA levels. The NDUFB6 rs540467 SNP modifies PA-mediated changes in insulin sensitivity, body composition and liver fat estimates in type 2 diabetes. Silencing Ndufb6 in myotubes reduced mitochondrial respiration and prevented rescue from palmitate-induced insulin resistance after EPS. A substantial proportion of humans with type 2 diabetes fails to respond to rising PA with increasing insulin sensitivity. This may at least partly relate to a polymorphism of the NDUFB6 gene, which may contribute to modulating mitochondrial function.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov, identifier NCT01055093. The trial was retrospectively registered on 25^th of January 2010.

Impact of APOE Alleles-by-Diet Interactions on Glycemic and Lipid Features- A Cross-Sectional Study of a Cohort of Type 2 Diabetes Patients from Western Mexico: Implications for Personalized Medicine

Purpose

To analyze clinically relevant interactions between the apolipoprotein E (APOE) ε2, ε3 and ε4 alleles and nutritional factors on glycemic control and lipid levels in a cohort of type 2 diabetes (T2D) patients from western Mexico.

Patients and Methods

In this cross-sectional study of the cohort of T2D patients, a total of 224 individuals were selected for interaction studies. Clinical and anthropometric data were obtained from pre-designed medical records. Dietary intake was assessed by validated three-day food consumption records. Biochemical measurements were determined by automated methods. APOE genotyping was performed by a real-time allelic discrimination assay. Gene–diet interactions were tested by corrected multiple linear regression analyses, which were adjusted by potential confounding factors such as age, sex, energy intake, BMI and anti-hyperglycemic therapy (Metformin, Glibenclamide or Insulin), and years with T2D.

Results

Seventy-six percent of patients with T2D were on Metformin therapy. The frequencies of the APOE alleles were ε2 (5.8%), ε3 (74.1%) and ε4 (20.1%). After statistical settings, significant APOE alleles-by-diet interactions in relation to the metabolic profile were found. Interestingly, higher blood levels of total cholesterol (p int. = 0.016), non-HDL-c (p int. = 0.024), and LDL-c (p int. = 0.030) were found only in carriers of the APOE ε2 allele with a low consumption of MUFA. In contrast, carriers of the APOE ε4 allele with a high ω-6:ω-3 PUFA ratio in the diet had higher %HbA1c blood concentrations (p int. = 0.035).

Conclusion

This study suggests a differential metabolic impact of APOE alleles on lipid/glycemic phenotypes depending on the dietary intake, with important potential implications in the personalized medicine and nutritional management of patients with type 2 diabetes mellitus.

Correlates of Insulin-Stimulated Glucose Disposal in Recent-Onset Type 1 and Type 2 Diabetes

CONTEXT AND OBJECTIVE

Not only type 2 diabetes (T2D), but also type 1 diabetes (T1D), can be associated with insulin resistance, as assessed using insulin-stimulated whole-body glucose disposal (M-value). We hypothesized that different factors would affect the M-value at the onset of T1D and T2D.

DESIGN AND PATIENTS

We examined 132 patients with T1D or T2D matched for sex, age, and body mass index with a known diabetes duration of <12 months. Multivariable linear regression analyses were applied to test the associations between glycemic control, blood lipid levels, adiponectin, and proinflammatory immune mediators and the M-value, obtained from the hyperinsulinemic-euglycemic clamp.

RESULTS

Despite comparable age, body mass index, and near-normoglycemic control, the mean M-value was lower in those with T2D than in those with T1D. Patients with T1D had a lower waist/hip ratio and serum triglycerides but higher serum adiponectin than patients with T2D. However, the circulating proinflammatory markers were not different. Even with adjustments for glucose-lowering treatments, the fasting blood glucose correlated negatively with the M-value in both groups. However, gamma-glutamyl transferase-independently of any treatments-correlated negatively only in T2D. In contrast, serum adiponectin correlated positively with the M-values.

CONCLUSIONS

Fasting glycemia correlated with insulin-stimulated glucose disposal in both diabetes types. However, altered liver and adipose tissue function were associated with insulin-stimulated glucose disposal only in T2D, underpinning the specific differences between these diabetes types.

Sex consideration in diet-biomarker-related indices: a systematic review

OBJECTIVE

An index of biomarkers derived from dietary factors (diet-biomarker-related index) identifies foods and nutrients that encompass physiological potentials and provides scientific evidence for dietary patterns that increase the risk of disease associated with specific biomarkers. Although men and women have different dietary patterns and physiological characteristics, sex is not often considered when investigators develop a diet-biomarker-related index. We aimed to review whether epidemiological studies developed diet-biomarker-related indices in a sex-specific way.

DESIGN

We systematically searched for epidemiological studies that developed diet-biomarker-related indices, including (i) biomarker prediction indices that include dietary factors as explanatory variables and (ii) dietary patterns to explain biomarker variations, in the PubMed and EMBASE databases. We qualitatively reviewed the sex consideration in index development.

RESULTS

We identified seventy-nine studies that developed a diet-biomarker-related index. We found that fifty-four studies included both men and women. Of these fifty-four studies, twenty-nine (53·7 %) did not consider sex, eleven (20·3 %) included sex in the development model, seven (13·0 %) considered sex but did not include sex in the development model, and seven (13·0 %) derived a diet-biomarker-related index for men and women separately. A list of selected dietary factors that explained levels of biomarkers generally differed by sex in the studies that developed a diet-biomarker-related index in a sex-specific way.

CONCLUSIONS

Most studies that included both men and women did not develop the diet-biomarker-related index in a sex-specific way. Further research is needed to identify whether a sex-specific diet-biomarker-related index is more predictive of the disease of interest than an index without sex consideration.

Food purchase patterns: empirical identification and analysis of their association with diet quality, socio-economic factors, and attitudes

Background

Empirically derived food purchase patterns provide information about which combinations of foods were purchased from households. The objective of this study was to identify what kinds of patterns exist, which level of diet quality they represent and which factors are associated with the patterns.

Methods

The study made use of representative German consumption data in which approximately 12 million food purchases from 13,125 households are recorded. In accordance with healthy diet criteria the food purchases were assigned to 18 food groups of the German Food Pyramid. Based on these groups a factor analysis with a principal component technique was applied to identify food patterns. For these patterns nutrient and energy densities were examined. Using regression analysis, associations between pattern scores and socio-economic as well as attitude variables, reflecting personal statements about healthy eating, were analyzed.

Results

In total, three food purchase patterns could be identified: a natural, a processed and a traditional one. The first one was characterized by a higher purchasing of natural foods, the second by an increased purchasing of processed foods and the third by a meat-oriented diet. In each pattern there were specific diet quality criteria that could be improved whereas others were in line with actual dietary guidelines. In addition to socio-demographic factors, attitudes were significantly associated with the purchase patterns.

Conclusions

The findings of this study are interesting from a public health perspective, as it can be assumed that measures focusing on specific aspects of diet quality are more promising than general ones. However, it is a major challenge to identify the population groups with their specific needs of improvement. As the patterns were associated with both socio-economic and attitude variables these grouping criteria could be used to define target groups.