Adherence to the Healthy Eating Index and Alternative Healthy Eating Index dietary patterns and mortality from all causes, cardiovascular disease and cancer: a meta-analysis of observational studies

2016 ◽  
Vol 30 (2) ◽  
pp. 216-226 ◽  
Author(s):  
S. Onvani ◽  
F. Haghighatdoost ◽  
P. J. Surkan ◽  
B. Larijani ◽  
L. Azadbakht
Keyword(s):  
Cardiovascular Disease ◽  
Healthy Eating ◽  
Dietary Patterns ◽  
Observational Studies ◽  
Meta Analysis ◽  
Healthy Eating Index ◽  
Alternative Healthy Eating Index

scholarly journals Dietary Inflammatory Index is associated with Healthy Eating Index, Alternative Healthy Eating Index, and dietary patterns among Iranian adults

2020 ◽  
Vol 34 (12) ◽  
Author(s):  
Zahra Asadi ◽  
Roshanak Ghaffarian Zirak ◽  
Mahdiyeh Yaghooti Khorasani ◽  
Mostafa Saedi ◽  
Seyed Mostafa Parizadeh ◽  
...  
Keyword(s):  
Healthy Eating ◽  
Dietary Patterns ◽  
Healthy Eating Index ◽  
Dietary Inflammatory Index ◽  
Inflammatory Index ◽  
Alternative Healthy Eating Index

scholarly journals Alternative Healthy Eating Index 2010, Dietary Inflammatory Index and risk of mortality: results from the Whitehall II cohort study and meta-analysis of previous Dietary Inflammatory Index and mortality studies

2017 ◽  
Vol 118 (3) ◽  
pp. 210-221 ◽  
Author(s):  
Nitin Shivappa ◽  
James R. Hebert ◽  
Mika Kivimaki ◽  
Tasnime Akbaraly
Keyword(s):  
Healthy Eating ◽  
Mortality Risk ◽  
Cancer Mortality ◽  
Meta Analysis ◽  
Healthy Eating Index ◽  
Dietary Inflammatory Index ◽  
Inflammatory Index ◽  
Risk Of Mortality ◽  
Alternative Healthy Eating Index ◽  
Cancer Mortality Risk

AbstractWe aimed to examine the association between the Alternative Healthy Eating Index updated in 2010 (AHEI-2010), the Dietary Inflammatory Index (DIITM) and risk of mortality in the Whitehall II study. We also conducted a meta-analysis on the DII-based results from previous studies to summarise the overall evidence. Data on dietary behaviour assessed by self-administered repeated FFQ and on mortality status were available for 7627 participants from the Whitehall II cohort. Cox proportional hazards regression models were performed to assess the association between cumulative average of AHEI-2010 and DII scores and mortality risk. During 22 years of follow-up, 1001 participants died (450 from cancer, 264 from CVD). Both AHEI-2010 (mean=48·7 (sd10·0)) and DII (mean=0·37 (sd1·41)) were associated with all-cause mortality. The fully adjusted hazard ratio (HR) persd, were 0·82; 95 % CI 0·76, 0·88 for AHEI-2010 and 1·18; 95 % CI 1·08, 1·29 for DII. Significant associations were also observed with cardiovascular and cancer mortality risk. For DII, a meta-analysis (using fixed effects) from this and four previous studies showed a positive association of DII score with all-cause (HR=1·04; 95 % CI 1·03, 1·05, 28 891deaths), cardiovascular (HR=1·05; 95 % CI 1·03, 1·07, 10 424 deaths) and cancer mortality (HR=1·05; 95 % CI 1·03, 1·07,n8269).The present study confirms the validity to assess overall diet through AHEI-2010 and DII in the Whitehall II cohort and highlights the importance of considering diet indices related to inflammation when evaluating all-cause, cardiovascular and cancer mortality risk.

Dietary Patterns And Risk Of Cancer: Current Evidence And Future Directions

2018 ◽  
Author(s):  
Fang Fang Zhang
Keyword(s):  
Healthy Eating ◽  
Cancer Incidence ◽  
Diet Quality ◽  
Dietary Patterns ◽  
Healthy Eating Index ◽  
Quality Indices ◽  
Alternative Healthy Eating Index ◽  
Incidence And Mortality ◽  
Risk Of Cancer ◽  
Diet Score

Dietary patterns capture the overall diet and its constituent foods and nutrients, representing a powerful approach to identifying the effect of nutrition on health and disease. In this review, we describe the two main approaches being used to characterize dietary patterns: a prior approach that defines dietary patterns using predefined diet quality indices, and a posterior approach that derives dietary patterns using factor or cluster analysis. Methods to define diet quality indices (Healthy Eating Index, Alternative Healthy Eating Index, Alternative Mediterranean Diet Score, Dietary Approaches to Stop Hypertension Score) are presented, and their similarities and differences are discussed among the different approaches. We review the recent evidence on the relationships between dietary patterns and cancer outcomes, including all-cancer incidence and mortality and the incidence of colorectal, breast, prostate, and lung cancers. Despite the different methods that are used to characterize dietary patterns in different studies, results consistently suggest that adherence to existing dietary guidelines is associated with a reduced risk of cancer incidence and mortality. Given the important role of dietary patterns in cancer prevention, clinicians need to consider providing appropriate nutrition counseling  to improve patients’ dietary patterns. Continuous efforts need to be devoted to better characterize the relationships between dietary patterns and cancer risk by studying specific cancer types, different cancer subtypes, and population subgroups, with a better approach that can accurately assess dietary patterns throughout the life cycle. This review contains 3 figures, 6 tables and 91 references Key words: Alternative Healthy Eating Index, breast cancer, cancer incidence, cancer mortality, cluster analysis, colorectal cancer, Dietary Approaches to Stop Hypertension, dietary patterns, diet quality index, factor analysis, Healthy Eating Index, lung cancer, Mediterranean Diet Score, prostate cancer, Recommended Food Score

Abstract 37: Healthy Eating Patterns and Risk of Cardiovascular Disease: Results From Three Large Prospective Cohort Studies

Circulation ◽  
2020 ◽  
Vol 141 (Suppl_1) ◽  
Author(s):  
Zhilei Shan ◽  
Yanping Li ◽  
Shilpa N Bhupathiraju ◽  
Dong Wang ◽  
Kathryn M Rexrode ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Healthy Eating ◽  
Dietary Patterns ◽  
Lower Risk ◽  
Healthy Eating Index ◽  
Health Study ◽  
Eating Patterns ◽  
Cvd Risk ◽  
Eating Pattern

Introduction: The 2015-2020 Dietary Guidelines for Americans (DGAs) recommend three major healthy dietary patterns: the Healthy US-Style Eating Pattern, the Healthy Mediterranean-Style Eating Pattern, and the Healthy Vegetarian Eating Pattern, for all Americans with diverse cultural and personal food traditions. However, few studies have systematically examined the potential differences in associations of adherence to these recommended dietary patterns with long-term risk of cardiovascular disease (CVD). Hypothesis: We hypothesized that all three DGA-recommended dietary patterns were associated with lower risk of CVD, coronary heart disease (CHD), and stroke. Method: We evaluated data on 74 661 women in the Nurses’ Health Study (NHS), 90 864 women in NHS II, and 41 837 men in the Health Professionals Follow-Up Study (HPFS), who had repeated dietary data and had no history of type 2 diabetes, CVD, or cancer at baseline. Using the food and nutrient components, we calculated the Healthy Eating Index (HEI)-2015, Alternate Mediterranean Diet score (AMED), Healthful Plant-based Diet Index (HPDI), to measure adherence to the Healthy US-Style Eating Pattern, Healthy Mediterranean-Style Eating Pattern, and Healthy Vegetarian Eating Pattern, respectively. Multivariable Cox proportional-hazards regression was used to assess the associations of healthy eating index with CVD risk. Results: We documented 9 262 incident CVD cases (6 628 CHD and 2 701 stroke) during 1 976 026 person years of follow-up in the NHS, 1 916 CVD cases (1 267 CHD and 660 stroke) during 2 173 162 person years of follow-up in NHS II, and 10 203 CVD cases (8 750 CHD and 1 775 stroke) during 873 053 person years of follow-up in HPFS. When comparing the highest to the lowest quintiles, the pooled HRs (95% CIs) of CVD were 0.80 (0.77 to 0.84) for HEI-2015, 0.83 (0.79 to 0.87) for AMED, and 0.85 (0.81 to 0.89) for HPDI (all P for trend <0.001). In addition, a 25-percentile increase in healthy eating scores was associated with 10% to 22% lower risk of CVD (pooled HR: HEI-2015, 0.78 [0.75 to 0.82]; AMED, 0.90 [0.88 to 0.92]; HPDI, 0.84 [0.81 to 0.88]). For CHD, the pooled HRs (95% CIs) per 20-percentile increase were 0.76 (0.73 to 0.80) for HEI-2015, 0.90 (0.87 to 0.92) for AMED, and 0.83 (0.79 to 0.87) for HPDI. For stroke, the pooled HRs (95% CIs) per 20-percentile increase were 0.86 (0.78 to 0.94) for HEI-2015, 0.90 (0.85 to 0.95) for AMED, and 0.90 (0.83 to 0.98) for HPDI. The inverse associations between healthy eating index and CVD risk persisted in analyses stratified by potential risk factors. Conclusions: In three large prospective cohorts with up to 32 years of follow-up, higher adherence to various healthy eating patterns was associated with lower risk of CVD, CHD, and stroke. Our findings support the DGA recommendations for multiple healthy eating patterns.

scholarly journals Mediterranean Diet and Healthy Eating in Subjects with Prediabetes from the Mollerussa Prospective Observational Cohort Study

Nutrients ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 252
Author(s):  
Mireia Falguera ◽  
Esmeralda Castelblanco ◽  
Marina Idalia Rojo-López ◽  
Maria Belén Vilanova ◽  
Jordi Real ◽  
...  
Keyword(s):  
Glucose Tolerance ◽  
Mediterranean Diet ◽  
Healthy Eating ◽  
Dietary Patterns ◽  
Normal Glucose Tolerance ◽  
Healthy Eating Index ◽  
Study Cohort ◽  
Cross Sectional ◽  
Normal Glucose ◽  
Multivariable Analyses

We aimed to assess differences in dietary patterns (i.e., Mediterranean diet and healthy eating indexes) between participants with prediabetes and those with normal glucose tolerance. Secondarily, we analyzed factors related to prediabetes and dietary patterns. This was a cross-sectional study design. From a sample of 594 participants recruited in the Mollerussa study cohort, a total of 535 participants (216 with prediabetes and 319 with normal glucose tolerance) were included. The alternate Mediterranean Diet score (aMED) and the alternate Healthy Eating Index (aHEI) were calculated. Bivariable and multivariable analyses were performed. There was no difference in the mean aMED and aHEI scores between groups (3.2 (1.8) in the normoglycemic group and 3.4 (1.8) in the prediabetes group, p = 0.164 for the aMED and 38.6 (7.3) in the normoglycemic group and 38.7 (6.7) in the prediabetes group, p = 0.877 for the aHEI, respectively). Nevertheless, women had a higher mean of aMED and aHEI scores in the prediabetes group (3.7 (1.9), p = 0.001 and 40.5 (6.9), p < 0.001, respectively); moreover, they had a higher mean of aHEI in the group with normoglycemia (39.8 (6.6); p = 0.001). No differences were observed in daily food intake between both study groups; consistent with this finding, we did not find major differences in nutrient intake between groups. In the multivariable analyses, the aMED and aHEI were not associated with prediabetes (odds ratio (OR): 1.19, 95% confidence interval (CI): 0.75–1.87; p = 0.460 and OR: 1.32, 95% CI: 0.83–2.10; p = 0.246, respectively); however, age (OR: 1.04, 95% CI: 1.02–1.05; p < 0.001), dyslipidemia (OR: 2.02, 95% CI: 1.27–3.22; p = 0.003) and body mass index (BMI) (OR: 1.09, 95% CI: 1.05–1.14; p < 0.001) were positively associated with prediabetes. Physical activity was associated with a lower frequency of prediabetes (OR: 0.48, 95% CI: 0.31–0.72; p = 0.001). In conclusion, subjects with prediabetes did not show a different dietary pattern compared with a normal glucose tolerance group. However, further research is needed on this issue.

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