No study has validated questionnaires for assessing easily calculable diet quality scores in Japan. The Brief-type self-administered Diet History Questionnaire (BDHQ) is widely used to assess dietary intake in Japan, while the Meal-based Diet History Questionnaire (MDHQ) assesses dietary intake for each meal (breakfast, lunch, dinner and snacks) and overall dietary intake. This study examined the relative validity of the BDHQ and MDHQ for assessing three diet quality scores in Japanese adults. A total of 111 women and 111 men aged 30–76 years completed the web MDHQ and BDHQ, followed by 4-non-consective-day weighed dietary records. The diet quality scores examined included the Diet Quality Score for Japanese (DQSJ), Dietary Approaches to Stop Hypertension (DASH) score and Alternate Mediterranean Diet (AMED) score. The means of the three scores for overall diet from the BDHQ were not significantly different from those from the dietary records in both sexes, whereas those from the MDHQ were higher than those from the dietary records, except for the DASH and AMED in women. Pearson’s correlation coefficients between both questionnaires and dietary records were 0·57–0·63 for DQSJ, 0·49–0·57 for DASH and 0·31–0·49 for AMED across both sexes and both questionnaires. For each meal, Pearson’s correlation coefficients between the MDHQ and dietary records ranged from 0·01 (DASH for snacks in women) to 0·55 (DQSJ for breakfast in men), with a median of 0·35. This study showed that the ability of the BDHQ and MDHQ to rank individuals was good for DQSJ and DASH and acceptable for AMED.

In studies that contain repeated measures of variables, longitudinal analysis accounting for time-varying covariates is one of the options. We aimed to explore longitudinal association between diet quality (DQ) and non-communicable diseases (NCDs). Participants from the 1973–1978 cohort of the Australian Longitudinal Study on Women’s Health (ALSWH) were included, if they; responded to survey 3 (S3, 2003, aged 25–30 years) and at least one survey between survey 4 (S4, 2006) and survey 8 (S8, 2018), were free of NCDs at or before S3, and provided dietary data at S3 or S5. Outcomes were coronary heart disease (CHD), hypertension (HT), asthma, cancer (except skin cancer), diabetes mellitus (DM), depression and/or anxiety, and multimorbidity (MM). Longitudinal modelling using generalised estimation equation (GEE) approach with time-invariant (S4), time-varying (S4–S8) and lagged (S3–S7) covariates were performed. The mean (± standard deviation) of Alternative Healthy Eating Index-2010 (AHEI-2010) of participants (n = 8022) was 51·6 ± 11·0 (range: 19–91). Compared to women with the lowest DQ (AHEI-2010 quintile 1), those in quintile 5 had reduced odds of NCDs in time-invariant model (asthma: OR (95 % CI): 0·77 (0·62–0·96), time-varying model (HT: 0·71 (0·50–0·99); asthma: 0·62 (0·51–0·76); and MM: 0·75 (0·58–0·97) and lagged model (HT: 0·67 (0·49–0·91); and asthma: 0·70 (0·57–0·85). Temporal associations between diet and some NCDs were more prominent in lagged GEE analyses. Evidence of diet as NCD prevention in women aged 25–45 years is evolving, and more studies that consider different longitudinal analyses are needed.

Despite evidence for favourable health outcomes associated with plant-based diets, a database containing the plant and animal content of all foods eaten is required to undertake a reliable assessment of plant-based diets within a population. This study aimed to expand an existing Australian food database to include the plant and animal content of all whole foods, beverages, multi-ingredient products and mixed dishes. Twenty-three plant- and animal-based food group classifications were first defined. The food servings per 100 g of each product were then systematically calculated using either a recipe-based approach, a food label-based approach, estimates based on similar products or online recipes. Overall, 4687 (83·5 %) foods and beverages were identified as plant or plant-containing products, and 3701 (65·9 %) were animal or animal-containing products. Results highlighted the versatility of plant and animal ingredients as they were found in various foods across many food categories, including savoury and sweet foods, as well as discretionary and core foods. For example, over 97 % of animal fat-containing foods were found in major food groups outside the AUSNUT 2011–2013 ‘fats and oils’ group. Surprisingly, fruits, nuts and seeds were present in a greater percentage of discretionary products than in core foods and beverages. This article describes a systematic approach that is suitable for the development of other novel food databases. This database allows more accurate quantitative estimates of plant and animal intakes, which is significant for future epidemiological and clinical research aiming to investigate plant-based diets and their related health outcomes.

Numerous observational studies have investigated associations between diet indices and health outcomes. Our aim was to systematically synthesise data that was previously summarised separately for each diet index in one umbrella review of all diet indices with sufficient evidence gained in systematic reviews and to assess the quality and strength of evidence for selected health outcomes. The MEDLINE, EMBASE and Scopus databases were systematically searched following the PRISMA guidelines through October 2021 for systematic reviews of observational studies investigating associations between adherence to diet indices and selected health outcomes (all-cause mortality, CVD incidence or mortality, type 2 diabetes mellitus incidence or mortality). Methodological quality and quality of evidence were assessed using the AMSTAR 2 and NutriGrade tools. The inclusion criteria were met by seven systematic reviews, entirely based on prospective cohort studies and reviewing five different diet indices – alternate healthy eating index (AHEI), dietary approaches to stop hypertension (DASH), dietary inflammatory index (DII), healthy eating index (HEI) and Mediterranean diet (MedDiet). All seven included systematic reviews showed that greater adherence to these diet indices reduces the risks of all-cause mortality, CVD incidence and mortality and type 2 diabetes mellitus incidence. Moderate meta-evidence was presented for AHEI and DASH for all outcomes, also for DII for all-cause mortality, CVD mortality and incidence, MedDiet for all-cause mortality and for HEI for CVD incidence and mortality. Our umbrella review provides further evidence for AHEI, DASH, DII and HEI diet indices to be used as predictors of selected health outcomes.

This study evaluated the association between dietary patterns, gas-related symptoms (GRS) and their impact on quality of life (QoL) in a representative sample (n 936) of the French adult population. During the 2018–2019 ‘Comportements et Consommations Alimentaires en France’ survey (Behaviors and Food Consumption in France), online evaluation of GRS in adult participants was performed using the validated Intestinal Gas Questionnaire (IGQ), which captures the perception of GRS and their impact on QoL via six symptom dimensions scores (range 0–100; 100 = worse) and a global score (mean of the sum of the six symptom dimensions scores). Socio-demographics, lifestyle parameters and dietary habits (7-d e-food diary) were also collected online. Quality of diet was determined using the Nutrient-Rich Food 9.3 (NRF9.3) score (range 0–900; 900 = best). Univariate and multivariate linear regression models were applied to identify factors associated with IGQ global score. K-means was used to identify clusters of subjects based on their dietary records. Data from 936 adults who completed both the IGQ and the food diary showed a mean IGQ global score of 11·9 (sd 11·2). Younger age and female sex were associated with a higher IGQ global score. Only 7 % of subjects reported no symptom at all and nearly 30 % of study participants reported a high impact of GRS on their QoL. Two dietary clusters were identified: cluster 1, characterised by a higher consumption of fruits and vegetables, lower sugars intake and higher NRF9.3 score and cluster 2, characterised by higher intake of sugars, lower intake in dietary fibres and lower NRF9.3 score. The IGQ global score was lower in cluster 1 and higher in cluster 2 v. the total sample average (P < 0·001). The prevalence of GRS in the French adult population is high and is associated with impaired QoL and dietary patterns. A change in food habits towards healthier patterns could help reducing the burden of GRS.

Diet quality indexes (DQI) are useful tools for assessing diet quality in relation to health and guiding delivery of personalised nutritional advice; however, existing DQI are limited in their applicability to older adults (aged ≥ 65 years). Therefore, this research aimed to develop a novel evidence-based DQI specific to older adults (DQI-65). Three DQI-65 variations were developed to assess the impacts of different component quantitation methods and inclusion of physical activity. These were Nutrient and Food-based DQI-65 (NFDQI-65), NFDQI-65 with Physical Activity (NFDQI-65+PA) and Food-based DQI-65 with Physical Activity (FDQI-65+PA). To assess their individual efficacy, the NFDQI-65, NFDQI-65+PA and FDQI-65+PA were explored alongside the validated Healthy Eating Index-2015 (HEI-2015) and Alternative Healthy Eating Index-2010 (AHEI-2010) using data from the cross-sectional UK National Diet and Nutrition Survey (NDNS) rolling programme. Scores for DQI-65 variations, the HEI-2015 and AHEI-2010 were calculated for adults ≥ 65 years from years 2–6 of the NDNS (n 871). Associations with nutrient intake, nutrient status and health markers were analysed using linear and logistic regression. Higher DQI-65 and HEI-2015 scores were associated with increased odds of meeting almost all our previously proposed age-specific nutritional recommendations, and with important health markers of importance for older adults, including lower BMI, lower medication use and lower C-reactive protein (P < 0·01). Few associations were observed for the AHEI-2010. This analysis suggests value of all three DQI-65 as measures of dietary quality in UK older adults. However, methodological limitations mean further investigations are required to assess validity and reliability of the DQI-65.

Diet quality indices (DQIs) are tools used to evaluate the overall diet quality against dietary guidelines or known healthy dietary patterns. This review aimed to evaluate DQIs and their validation processes to facilitate decision making in the selection of appropriate DQI for use in Australian contexts. A search of CINAHL, PubMed and Scopus electronic databases was conducted for studies published between January 2010 and May 2020, which validated a DQI, measuring > 1 dimension of diet quality (adequacy, balance, moderation, variety) and was applicable to the Australian context. Data on constructs, scoring, weighting and validation methods (construct validity, criterion validity, reliability and reproducibility) were extracted and summarised. The quality of the validation process was evaluated using COnsensus-based Standards for the selection of health Measurement INstruments Risk of Bias and Joanna Briggs Appraisal checklists. The review identified twenty-seven indices measuring adherence to: national dietary guidelines (n 13), Mediterranean Diet (n 8) and specific population recommendations and chronic disease risk (n 6). Extensiveness of the validation process varied widely across and within categories. Construct validity was the most strongly assessed measurement property, while evaluation of measurement error was frequently inadequate. DQIs should capture multiple dimensions of diet quality, possess a reliable scoring system and demonstrate adequate evidence in their validation framework to support use in the intended context. Researchers need to understand the limitations of newly developed DQIs and interpret results in view of the validation evidence. Future research on DQIs is indicated to improve evaluation of measurement error, reproducibility and reliability.

Nutritional studies shifted the focus of attention to the analysis of food quality, addressing general diet considering the foods, food groups and nutrients included. This study evaluates the association between diet quality index, food and nutrient intake and metabolic parameters of adolescents from Recife, northeastern Brazil. It is a cross-sectional study involving adolescents aged 12 to 19 years. Food intake was assessed using the FFQ to estimate the adapted Diet Quality Index for Adolescents for Brazilians (DQIA-BR-A). The analysis included metabolic parameters (glucose, lipid profile, apo A1 and B, α-1-acid glycoprotein, retinol, β-carotene, α-tocopherol, 25-hydroxyvitamin D and parathormone). Multiple linear regression analysis between the DQIA-BR-A and daily nutrient intake showed a positive correlation (R2 adjusted = 0·29) for linoleic fatty acid, Ca and folate and a negative correlation for oleic fatty acid, carbohydrates and vitamins B2 and C, in addition to a low correlation (R2 adjusted < 0·07) with all metabolic parameters. However, the DQIA-BR-A correlated significantly (R2 adjusted = 0·62; P < 0·001) with food intake. In this way, the DQIA-BR-A can be considered as an accurate and useful instrument for assessing the overall quality of adolescent diets. The diet of the adolescents was considered to be of moderate quality. Changes are required to ensure a balanced diet, considering the high-sugar intake and consumption of sweets as well as the low consumption of vegetables, milk and dairy products, oils, fats and seeds. Such changes should prioritise the consumption of foods rich in essential fatty acids and poor in saturated fat.

High-quality diets have been found to be beneficial in preventing long-term weight gain. However, concurrent changes in diet quality and body weight over time have rarely been reported. We examined the association between 10-year changes in diet quality and body weight in the Multiethnic Cohort Study. Analyses included 53 977 African Americans, Native Hawaiians, Japanese Americans, Latinos and Whites, who completed both baseline (1993–1996, 45–69 years) and 10-year follow-up (2003–2008) surveys including a FFQ and had no history of heart disease or cancer. Using multivariable regression, weight changes were regressed on changes in four diet quality indexes, Healthy Eating Index-2015, Alternative Healthy Eating Index-2010, alternate Mediterranean Diet and Dietary Approaches to Stop Hypertension scores. Mean weight change over 10 years was 1·2 (sd 6·8) kg in men and 1·5 (sd 7·2) kg in women. Compared with stable diet quality (< 0·5 sd change), the greatest increase (≥ 1 sd increase) in the diet scores was associated with less weight gain (by 0·55–1·17 kg in men and 0·62–1·31 kg in women). Smaller weight gain with improvement in diet quality was found in most subgroups by race/ethnicity, baseline age and baseline BMI. The inverse association was stronger in younger age and higher BMI groups. Ten-year improvement in diet quality was associated with a smaller weight gain, which varied by race/ethnicity and baseline age and BMI. Our findings suggest that maintaining a high-quality diet and improving diet quality over time may prevent excessive weight gain.

We conducted a narrative review on the interaction between dietary patterns with demographic and lifestyle variables in relation to health status assessment. The food pattern has the advantage of taking into account the correlations that may exist between foods or groups of foods, but also between nutrients. It is an alternative and complementary approach in analysing the relationship between nutrition and the risk of chronic diseases. For the determination of dietary patterns one can use indices/scores that evaluate the conformity of the diet with the nutrition guidelines or the established patterns (a priori approach). The methods more commonly used are based on exploratory data (a posteriori): cluster analysis and factor analysis. Dietary patterns may vary according to sex, socio-economic status, ethnicity, culture and other factors, but more, they may vary depending on different associations between these factors. The dietary pattern exerts its effects on health in a synergistic way or even in conjunction with other lifestyle factors, and we can therefore refer to a ‘pattern of lifestyle’.

This review evaluates evidence on dietary interventions for cancer survivors giving an overview of people's views and preferences for service attributes and provides a narrative review. After cancer, people often want to change their diet and there is a plethora of evidence why dietary optimisation would be beneficial. However, cancer survivors have different preferences about attributes of services including: place, person and communication mode. Randomised control trials have been reviewed to provide a narrative summary of evidence of dietary interventions. Most studies were on survivors of breast cancer, with a few on colorectal, prostate and gynaecological survivors. Telephone interventions were the most frequently reported means of providing advice and dietitians were most likely to communicate advice. Dietary assessment methods used were FFQ, food diaries and 24-h recalls. Dietary interventions were shown to increase intake of fruit and vegetables, dietary fibre, and improve diet quality in some studies but with contradictory findings in others. Telephone advice increased fruit and vegetable intake primarily in women with breast cancer and at some time points in people after colorectal cancer, but findings were inconsistent. Findings from mail interventions were contradictory, although diet quality improved in some studies. Web-based and group sessions had limited benefits. There is some evidence that dietary interventions improve diet quality and some aspects of nutritional intake in cancer survivors. However, due to contradictory findings between studies and cancer sites, short term follow-up and surrogate endpoints it is difficult to decipher the evidence base.

Tools, called ‘diet/dietary quality indices’, evaluate the level of adherence to a specified pattern or a set of recommendations in populations. Yet, there are no review studies providing unanimous comprehensive results of dietary indices on obesity. We reviewed observational studies, focusing on the association of diet quality indices with general obesity or abdominal obesity in adults. We systematically conducted a search in all English language publications available on MEDLINE, ISI Web of Science and Embase between January 1990 and January 2016. Among the wide variety of indices and weight-derived variables, studies with dietary-guideline-based indices and mean changes for weight gain or OR for general obesity and abdominal obesity were selected. From a total of 479 articles, thirty-four studies were selected for the current review, ten of which had prospective designs and twenty-six had cross-sectional designs. Associations of weight status with the original Healthy Eating Index (HEI) and other versions of the HEI including alternative HEI, HEI-2005 and HEI-05 were examined in thirteen studies, with ten studies revealing significant associations. The HEI was a better general obesity predictor in men than in women. Diet scores lacked efficacy in assessing overall diet quality and demonstrated no significant findings in developing countries, in comparison with US populations. In addition, indices based on dietary diversity scores were directly associated with weight gain. Despite the insufficient evidence to draw definitive conclusions about the relation between dietary indices and obesity, HEI was found to be inversely associated with obesity and diversity-based indices were positively associated with obesity.

This study aimed to examine the association between vitamin B6, folate and vitamin B12 biomarkers and plasma fatty acids in European adolescents. A subsample from the Healthy Lifestyle in Europe by Nutrition in Adolescence study with valid data on B-vitamins and fatty acid blood parameters, and all the other covariates used in the analyses such as BMI, Diet Quality Index, education of the mother and physical activity assessed by a questionnaire, was selected resulting in 674 cases (43 % males). B-vitamin biomarkers were measured by chromatography and immunoassay and fatty acids by enzymatic analyses. Linear mixed models elucidated the association between B-vitamins and fatty acid blood parameters (changes in fatty acid profiles according to change in 10 units of vitamin B biomarkers). DHA, EPA) and n-3 fatty acids showed positive associations with B-vitamin biomarkers, mainly with those corresponding to folate and vitamin B12. Contrarily, negative associations were found with n-6:n-3 ratio, trans-fatty acids and oleic:stearic ratio. With total homocysteine (tHcy), all the associations found with these parameters were opposite (for instance, an increase of 10 nmol/l in red blood cell folate or holotranscobalamin in females produces an increase of 15·85 µmol/l of EPA (P value <0·01), whereas an increase of 10 nmol/l of tHcy in males produces a decrease of 2·06 µmol/l of DHA (P value <0·05). Positive associations between B-vitamins and specific fatty acids might suggest underlying mechanisms between B-vitamins and CVD and it is worth the attention of public health policies.