The aim of the present systematic review and meta-analysis was to gain further insight into the effects of adherence to Mediterranean Diet (MedD) on risk of overall cancer mortality, risk of ...different types of cancer, and cancer mortality and recurrence risk in cancer survivors. Literature search was performed using the electronic databases PubMed, and Scopus until 25 August 2017. We included randomized trials (RCTs), cohort (for specific tumors only incidence cases were used) studies, and case-control studies. Study-specific risk ratios, hazard ratios, and odds ratios (RR/HR/OR) were pooled using a random effects model. Observational studies (cohort and case-control studies), and intervention trials were meta-analyzed separately. The updated review process showed 27 studies that were not included in the previous meta-analysis (total number of studies evaluated: 83 studies). An overall population of 2,130,753 subjects was included in the present update. The highest adherence score to a MedD was inversely associated with a lower risk of cancer mortality (RR
: 0.86, 95% CI 0.81 to 0.91,
² = 82%;
= 14 studies), colorectal cancer (RR
: 0.82, 95% CI 0.75 to 0.88,
² = 73%;
= 11 studies), breast cancer (RR
: 0.43, 95% CI 0.21 to 0.88,
= 1 study) (RR
: 0.92, 95% CI 0.87 to 0.96,
² = 22%,
= 16 studies), gastric cancer (RR
: 0.72, 95% CI 0.60 to 0.86,
² = 55%;
= 4 studies), liver cancer (RR
: 0.58, 95% CI 0.46 to 0.73,
² = 0%;
= 2 studies), head and neck cancer (RR
: 0.49, 95% CI 0.37 to 0.66,
² = 87%;
= 7 studies), and prostate cancer (RR
: 0.96, 95% CI 0.92 to 1.00,
² = 0%;
= 6 studies). Among cancer survivors, the association between the adherence to the highest MedD category and risk of cancer mortality, and cancer recurrence was not statistically significant. Pooled analyses of individual components of the MedD revealed that the protective effects appear to be most attributable to fruits, vegetables, and whole grains. The updated meta-analysis confirms an important inverse association between adherence to a MedD and cancer mortality and risk of several cancer types, especially colorectal cancer. These observed beneficial effects are mainly driven by higher intakes of fruits, vegetables, and whole grains. Moreover, we were able to report for the first time a small decrease in breast cancer risk (6%) by pooling seven cohort studies.
In previous meta-analyses of prospective observational studies, we investigated the association between food groups and risk of chronic disease.
The aim of the present network meta-analysis (NMA) was ...to assess the effects of these food groups on intermediate-disease markers across randomized intervention trials.
Literature searches were performed until January 2018. The following inclusion criteria were defined a priori: 1) randomized trial (≥4 wk duration) comparing ≥2 of the following food groups: refined grains, whole grains, nuts, legumes, fruits and vegetables, eggs, dairy, fish, red meat, and sugar-sweetened beverages (SSBs); 2) LDL cholesterol and triacylglycerol (TG) were defined as primary outcomes; total cholesterol, HDL cholesterol, fasting glucose, glycated hemoglobin, homeostasis model assessment insulin resistance, systolic and diastolic blood pressure, and C-reactive protein were defined as secondary outcomes. For each outcome, a random NMA was performed, and for the ranking, the surface under the cumulative ranking curves (SUCRA) was determined.
A total of 66 randomized trials (86 reports) comparing 10 food groups and enrolling 3595 participants was identified. Nuts were ranked as the best food group at reducing LDL cholesterol (SUCRA: 93%), followed by legumes (85%) and whole grains (70%). For reducing TG, fish (97%) was ranked best, followed by nuts (78%) and red meat (72%). However, these findings are limited by the low quality of the evidence. When combining all 10 outcomes, the highest SUCRA values were found for nuts (66%), legumes (62%), and whole grains (62%), whereas SSBs performed worst (29%).
The present NMA provides evidence that increased intake of nuts, legumes, and whole grains is more effective at improving metabolic health than other food groups. For the credibility of diet-disease relations, high-quality randomized trials focusing on well-established intermediate-disease markers could play an important role. This systematic review was registered at PROSPERO (www.crd.york.ac.uk/PROSPERO) as CRD42018086753.
This meta-analysis summarizes the evidence of a prospective association between the intake of foods whole grains, refined grains, vegetables, fruit, nuts, legumes, eggs, dairy, fish, red meat, ...processed meat, and sugar-sweetened beverages (SSBs) and risk of general overweight/obesity, abdominal obesity, and weight gain. PubMed and Web of Science were searched for prospective observational studies until August 2018. Summary RRs and 95% CIs were estimated from 43 reports for the highest compared with the lowest intake categories, as well as for linear and nonlinear relations focusing on each outcome separately: overweight/obesity, abdominal obesity, and weight gain. The quality of evidence was evaluated with use of the NutriGrade tool. In the dose-response meta-analysis, inverse associations were found for whole-grain (RRoverweight/obesity: 0.93; 95% CI: 0.89, 0.96), fruit (RRoverweight/obesity: 0.93; 95% CI: 0.86, 1.00; RRweight gain: 0.91; 95% CI: 0.86, 0.97), nut (RRabdominal obesity: 0.42; 95% CI: 0.31, 0.57), legume (RRoverweight/obesity: 0.88; 95% CI: 0.84, 0.93), and fish (RRabdominal obesity: 0.83; 95% CI: 0.71, 0.97) consumption and positive associations were found for refined grains (RRoverweight/obesity: 1.05; 95% CI: 1.00, 1.10), red meat (RRabdominal obesity: 1.10; 95% CI: 1.04, 1.16; RRweight gain: 1.14; 95% CI: 1.03, 1.26), and SSBs (RRoverweight/obesity: 1.05; 95% CI: 1.00, 1.11; RRabdominal obesity: 1.12; 95% CI: 1.04, 1.20). The dose-response meta-analytical findings provided very low to low quality of evidence that certain food groups have an impact on different measurements of adiposity risk. To improve the quality of evidence, better-designed observational studies, inclusion of intervention trials, and use of novel statistical methods (e.g., substitution analyses or network meta-analyses) are needed.
Background: Despite growing evidence for food-based dietary patterns' potential to reduce cardiovascular disease risk, knowledge about the amounts of food associated with the greatest change in risk ...of specific cardiovascular outcomes and about the quality of meta-evidence is limited. Therefore, the aim of this meta-analysis was to synthesize the knowledge about the relation between intake of 12 major food groups (whole grains, refined grains, vegetables, fruits, nuts, legumes, eggs, dairy, fish, red meat, processed meat, and sugar-sweetened beverages SSB) and the risk of coronary heart disease (CHD), stroke and heart failure (HF).
Methods: We conducted a systematic search in PubMed and Embase up to March 2017 for prospective studies. Summary risk ratios (RRs) and 95% confidence intervals (95% CI) were estimated using a random effects model for highest versus lowest intake categories, as well as for linear and non-linear relationships.
Results: Overall, 123 reports were included in the meta-analyses. An inverse association was present for whole grains (RR
CHD
: 0.95 (95% CI: 0.92-0.98), RR
HF
: 0.96 (0.95-0.97)), vegetables and fruits (RR
CHD
: 0.97 (0.96-0.99), and 0.94 (0.90-0.97); RR
stroke
: 0.92 (0.86-0.98), and 0.90 (0.84-0.97)), nuts (RR
CHD
: 0.67 (0.43-1.05)), and fish consumption (RR
CHD
: 0.88 (0.79-0.99), RR
stroke
: 0.86 (0.75-0.99), and RR
HF
: 0.80 (0.67-0.95)), while a positive association was present for egg (RR
HF
: 1.16 (1.03-1.31)), red meat (RR
CHD
: 1.15 (1.08-1.23), RR
stroke
: 1.12 (1.06-1.17), RR
HF
: 1.08 (1.02-1.14)), processed meat (RR
CHD
: 1.27 (1.09-1.49), RR
stroke
: 1.17 (1.02-1.34), RR
HF
: 1.12 (1.05-1.19)), and SSB consumption (RR
CHD
: 1.17 (1.11-1.23), RR
stroke
: 1.07 (1.02-1.12), RR
HF
: 1.08 (1.05-1.12)) in the linear dose-response meta-analysis. There were clear indications for non-linear dose-response relationships between whole grains, fruits, nuts, dairy, and red meat and CHD.
Conclusion: An optimal intake of whole grains, vegetables, fruits, nuts, legumes, dairy, fish, red and processed meat, eggs and SSB showed an important lower risk of CHD, stroke, and HF.
Purpose
We aimed to synthesize the evidence on the relation between different types of potato consumption with risk of all-cause mortality, coronary heart disease (CHD), stroke, type 2 diabetes ...(T2D), colorectal cancer (CRC), and hypertension.
Methods
Systematic searches until May 2018 were conducted in PubMed, Scopus, and Web of Science. Random effects meta-analyses comparing extreme categories, linear and non-linear dose–response analyses were conducted.
Results
Twenty-eight reports were identified. Only total potato consumption was available for some endpoints which showed no associations with all-cause mortality (RR: 0.88, 95% CI 0.69–1.12), CHD (RR: 1.03, 95% CI 0.96–1.09), stroke (RR: 0.98, 95% CI 0.93–1.03), and CRC (RR: 1.05, 95% CI 0.92–1.20) per one daily/serving (150 g/day) increase. Consumption of one daily serving of boiled/baked/mashed-potatoes was not associated with risk of hypertension (RR: 1.08, 95% CI 0.96–1.21), but slightly with the risk of T2D (RR: 1.09, 95% 1.01–1.18). Positive associations for the risk of T2D (RR: 1.66, 95% CI 1.43–1.94) and hypertension (RR: 1.37, 95% CI 1.15–1.63) were observed for each 150 g/day increase in French-fries consumption. The quality of evidence was rated mostly low (moderate quality of evidence for the risk-associations of French-fries).
Conclusion
Total potato consumption is not related to risk for many chronic diseases but could pose a small increase in risk for T2D if consumed boiled. A clear risk relation was found between French-fries consumption and risk of T2D and hypertension. For several outcomes, the impact of different preparation procedures could not be assessed.
Suboptimal diet is one of the most important factors in preventing early death and disability worldwide.
The aim of this meta-analysis was to synthesize the knowledge about the relation between ...intake of 12 major food groups, including whole grains, refined grains, vegetables, fruits, nuts, legumes, eggs, dairy, fish, red meat, processed meat, and sugar-sweetened beverages, with risk of all-cause mortality.
We conducted a systematic search in PubMed, Embase, and Google Scholar for prospective studies investigating the association between these 12 food groups and risk of all-cause mortality. Summary RRs and 95% CIs were estimated with the use of a random effects model for high-intake compared with low-intake categories, as well as for linear and nonlinear relations. Moreover, the risk reduction potential of foods was calculated by multiplying the RR by optimal intake values (serving category with the strongest association) for risk-reducing foods or risk-increasing foods, respectively.
With increasing intake (for each daily serving) of whole grains (RR: 0.92; 95% CI: 0.89, 0.95), vegetables (RR: 0.96; 95% CI: 0.95, 0.98), fruits (RR: 0.94; 95% CI: 0.92, 0.97), nuts (RR: 0.76; 95% CI: 0.69, 0.84), and fish (RR: 0.93; 95% CI: 0.88, 0.98), the risk of all-cause mortality decreased; higher intake of red meat (RR: 1.10; 95% CI: 1.04, 1.18) and processed meat (RR: 1.23; 95% CI: 1.12, 1.36) was associated with an increased risk of all-cause mortality in a linear dose-response meta-analysis. A clear indication of nonlinearity was seen for the relations between vegetables, fruits, nuts, and dairy and all-cause mortality. Optimal consumption of risk-decreasing foods results in a 56% reduction of all-cause mortality, whereas consumption of risk-increasing foods is associated with a 2-fold increased risk of all-cause mortality.
Selecting specific optimal intakes of the investigated food groups can lead to a considerable change in the risk of premature death.
The aim of this systematic review and meta-analysis was to summarize the evidence on the relation of the intakes of 12 major food groups, including whole grains, refined grains, vegetables, fruits, ...nuts, legumes, eggs, dairy, fish, red meat, processed meat, and sugar-sweetened beverages (SSBs) with the risk of hypertension. PubMed, Scopus, and Web of Science were searched systematically until June 2017 for prospective studies having quantitatively investigated the above-mentioned foods. We conducted meta-analysis on the highest compared with the lowest intake categories and linear and nonlinear dose-response meta-analyses to analyze the association. Summary RRs and 95% CIs were estimated by using a random-effects model. Overall, 28 reports were included in the meta-analysis. An inverse association for the risk of hypertension was observed for 30 g whole grains/d (RR: 0.92; 95% CI: 0.87, 0.98), 100 g fruits/d (RR: 0.97; 95% CI: 0.96, 0.99), 28 g nuts/d (RR: 0.70; 95% CI: 0.45, 1.08), and 200 g dairy/d (RR: 0.95; 95% CI: 0.94, 0.97), whereas a positive association for 100 g red meat/d (RR: 1.14; 95% CI: 1.02, 1.28), 50 g processed meat/d (RR: 1.12; 95% CI: 1.00, 1.26), and 250 mL SSB/d (RR: 1.07; 95% CI: 1.04, 1.10) was seen in the linear dose-response meta-analysis. Indication for nonlinear relations of the intakes of whole grains, fruits, fish, and processed meats with the risk of hypertension was detected. In summary, this comprehensive dose-response meta-analysis of 28 reports identified optimal intakes of whole grains, fruits, nuts, legumes, dairy, red and processed meats, and SSBs related to the risk of hypertension. These findings need to be seen under the light of very-low to low quality of meta-evidence. However, the findings support the current dietary guidelines in the prevention of hypertension.
Principal component analysis (PCA) is a widely used exploratory method in epidemiology to derive dietary patterns from habitual diet. Such dietary patterns seem to originate from intakes on multiple ...days and eating occasions. Therefore, analyzing food intake of study populations with different levels of food consumption can provide additional insights as to how habitual dietary patterns are formed.
We analyzed the food intake data of German adults in terms of the relations among food groups from three 24-h dietary recalls (24hDRs) on the habitual, single-day, and main-meal levels, and investigated the contribution of each level to the formation of PCA-derived habitual dietary patterns.
Three 24hDRs were collected in 2010–2012 from 816 adults for an European Prospective Investigation into Cancer and Nutrition (EPIC)–Potsdam subcohort study. We identified PCA-derived habitual dietary patterns and compared cross-sectional food consumption data in terms of correlation (Spearman), consistency (intraclass correlation coefficient), and frequency of consumption across all days and main meals. Contribution to the formation of the dietary patterns was obtained through Spearman correlation of the dietary pattern scores.
Among the meals, breakfast appeared to be the most consistent eating occasion within individuals. Dinner showed the strongest correlations with “Prudent” (Spearman correlation = 0.60), “Western” (Spearman correlation = 0.59), and “Traditional” (Spearman correlation = 0.60) dietary patterns identified on the habitual level, and lunch showed the strongest correlations with the “Cereals and legumes” (Spearman correlation = 0.60) habitual dietary pattern.
Higher meal consistency was related to lower contributions to the formation of PCA-derived habitual dietary patterns. Absolute amounts of food consumption did not strongly conform to the habitual dietary patterns by meals, suggesting that these patterns are formed by complex combinations of variable food consumption across meals. Dinner showed the highest contribution to the formation of habitual dietary patterns. This study provided information about how PCA-derived dietary patterns are formed and how they could be influenced.
The current state of knowledge regarding the association of dairy products and weight gain, overweight, and obesity is based on studies reporting contradicting and inconclusive results. The aim of ...the present study was thus to clarify the link between dairy consumption in relation to changes in anthropometric measures/adiposity by a meta-analytical approach.
For the meta-analysis PubMed, EMBASE, Web of Sciences, and google scholar were searched by two independent authors up to May 2016 with no restriction to language or calendar date. Prospective cohort studies reporting about intake of dairy consumption (including milk, yogurt, cheese, butter) and changes in body weight or waist circumference, risk of overweight, obesity, or weight gain were eligible. Pooled effects were calculated using a random effects model, and also a fixed effect model for sensitivity analysis. Due to the heterogeneity of statistical analytical approaches of the studies the analysis were done separately for beta-coefficients of changes in body weight and/or waist circumference per serving of dairy, for differences in weight gain/gain in waist circumference when comparing extreme categories of dairy consumption, and for odds ratios in regard to weight gain, overweight/obesity, or abdominal obesity.
24 studies (27 reports) met the inclusion criteria for the systematic review, and 22 studies provided sufficient data for inclusion in the meta-analysis. The meta-analysis of the five studies on changes in body weight per serving of dairy no significant results could be found for whole fat dairy and low fat dairy. However, there was inverse association between changes in body weight for each serving's increase of yogurt (beta: -40.99 gram/year, 95% CI, -48.09 to -33.88), whereas each serving's increase of cheese was positively associated (beta: -10.97 gram/year, 95% CI, 2.86 to 19.07). Furthermore, the highest dairy intake category was associated with a reduced risk of abdominal obesity (OR: 0.85; 95% CI, 0.76 to 0.95), and risk of overweight (OR: 0.87; 95% CI, 0.76 to 1.00) compared to the lowest intake category. No significant association could be observed for risk of weight gain.
In summary the results of the meta-analysis still reflect that dairy consumption was not positively related to changes in body weight. Yogurt was the only dairy food that showed some evidence for a beneficial effect, where higher intakes were inversely associated a reduced risk of obesity, changes in body weight or waist circumference. Further research is needed, since the overall interpretation of the results is limited by heterogeneous risk estimates.
The objective of this study was to develop a scoring system (NutriGrade) to evaluate the quality of evidence of randomized controlled trial (RCT) and cohort study meta-analyses in nutrition research, ...building upon previous tools and expert recommendations. NutriGrade aims to assess the meta-evidence of an association or effect between different nutrition factors and outcomes, taking into account nutrition research–specific requirements not considered by other tools. In a pretest study, 6 randomly selected meta-analyses investigating diet–disease relations were evaluated with NutriGrade by 5 independent raters. After revision, NutriGrade was applied by the same raters to 30 randomly selected meta-analyses in the same thematic area. The reliability of ratings of NutriGrade items was calculated with the use of a multirater κ, and reliability of the total (summed scores) was calculated with the use of intraclass correlation coefficients (ICCs). The following categories for meta-evidence evaluation were established: high (8–10), moderate (6–7.99), low (4–5.99), and very low (0–3.99). The NutriGrade scoring system (maximum of 10 points) comprises the following items: 1) risk of bias, study quality, and study limitations, 2) precision, 3) heterogeneity, 4) directness, 5) publication bias, 6) funding bias, 7) study design, 8) effect size, and 9) dose-response. The NutriGrade score varied between 2.9 (very low meta-evidence) and 8.8 (high meta-evidence) for meta-analyses of RCTs, and it ranged between 3.1 and 8.8 for meta-analyses of cohort studies. The κ value of the ratings for each scoring item varied from 0.32 (95% CI: 0.22, 0.42) for risk of bias for cohort studies and 0.95 (95% CI: 0.91, 0.99) for study design, with a mean κ of 0.66 (95% CI: 0.53, 0.79). The ICC of the total score was 0.81 (95% CI: 0.69, 0.90). The NutriGrade scoring system showed good agreement and reliability. The initial findings regarding the performance of this newly established scoring system need further evaluation in independent analyses.
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