There is an urgent need to identify and develop cross-sectoral policies which promote and support a healthy, safe and sustainable food system. To help shape the political agenda, a critical first step is a shared definition of such a system among policy makers across relevant sectors. The aim of the present study was to determine how Australian policy actors define, and contribute to, a healthy, safe and sustainable food system.

A Delphi survey, consisting of two rounds, was conducted. Participants were asked how they define, and contribute to, a healthy, safe and sustainable food system (Round 1) and indicate their level of agreement with summary statements (Round 2).

This was an online Delphi survey conducted in Australia.

Twenty-nine and fourteen multisectoral and multilevel policy makers completed Round 1 and Round 2, respectively.

The definition included food processing regulation, environmentally friendly food production and access to nutritious food. All agreed that it was important for them to improve access and supply of healthy food and ensure healthy planning principles are applied.

There were cross-sectoral differences in definitions and contributions; however, critical consensus was achieved. The study contributes to the definition of key elements of a cross-sectoral food and nutrition policy to meet today’s environmental, health, social and economic challenges; however, further research using a more representative multisectoral sample is warranted.

To conduct nutrition-related analyses on large-scale health surveys, two aspects of the survey must be incorporated into the analysis: the sampling weights and the sample design; a practice which is not always observed. The present paper compares three analyses: (1) unweighted; (2) weighted but not accounting for the complex sample design; and (3) weighted and accounting for the complex design using replicate weights.

Descriptive statistics are computed and a logistic regression investigation of being overweight/obese is conducted using Stata.

Cross-sectional health survey with complex sample design where replicate weights are supplied rather than the variables containing sample design information.

Responding adults from the National Nutrition and Physical Activity Survey (NNPAS) part of the Australian Health Survey (2011–2013).

Unweighted analysis produces biased estimates and incorrect estimates of se. Adjusting for the sampling weights gives unbiased estimates but incorrect se estimates. Incorporating both the sampling weights and the sample design results in unbiased estimates and the correct se estimates. This can affect interpretation; for example, the incorrect estimate of the OR for being a current smoker in the unweighted analysis was 1·20 (95 % CI 1·06, 1·37), t= 2·89, P = 0·004, suggesting a statistically significant relationship with being overweight/obese. When the sampling weights and complex sample design are correctly incorporated, the results are no longer statistically significant: OR = 1·06 (95 % CI 0·89, 1·27), t = 0·71, P = 0·480.

Correct incorporation of the sampling weights and sample design is crucial for valid inference from survey data.

To examine associations between Canadian adolescents’ sugar-sweetened beverage (SSB) consumption and several school food environment characteristics, and to investigate differences in these characteristics between schools in provinces with voluntary (Alberta) v. mandatory (Ontario) provincial school nutrition policies.

We used a questionnaire to assess the number of weekdays participants consumed three SSB categories (soft drinks, sweetened coffees/teas, energy drinks) and various sociodemographic and behavioural characteristics. We examined the in-school water fountain accessibility, vending machines’ contents and presence of various food outlets within schools’ 1 km buffer. We developed hierarchical Poisson regression models to identify associations between student- and school-level characteristics and students’ SSB outcomes.

Alberta and Ontario, Canada.

Adolescents (n 41 829) from eighty-nine secondary schools.

Compared with their Ontarian counterparts, Albertan participants had a significantly higher rate of SSB intake across all drink categories and SSB availability was significantly greater in Albertan schools’ vending machines. Availability of sweetened coffees/teas in school vending machines and access to restaurants within the school’s 1 km buffer were associated with increased SSB intake in three of the final models. Overall, the school food environment-level characteristics examined had a modest to negligible impact on student days of SSB intake.

We identified that the school food environment characteristics examined here had little impact on adolescents’ days of SSB consumption. While schools should adopt or maintain a comprehensive policy approach to discourage students’ SSB intake, population-level interventions focusing on other contexts (e.g. home and community) are needed to complement existing school-based interventions.

To develop and test a scale for healthy eating practices measurement according to the Dietary Guidelines for the Brazilian Population recommendations.

Methodological study. The current Brazilian food-based dietary guideline highlights the importance of choosing foods, combining foods to create meals and modes of eating. These recommendations formed the main domains of the scale and served as a basis for the development of ninety-six items, each with a 4-point Likert response option. Content and face validity were tested. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were performed to determine construct validity. Internal consistency was determined using α and ω coefficients, and reproducibility was tested using test–retest.

Brazil.

A ten-member expert panel was used to assess content validity. Adults aged 18–60 years were included in the face validity (n 20), EFA (n 352), CFA and reliability tests (n 900).

Of the ninety-six initial items, twenty-four were excluded and fifty-five were reworded following the content and face validations. EFA detected a four-domain structure (Food choices, Modes of eating, Planning and Domestic organization), which explained 41 % of the variance. CFA led to a final twenty-four-item model with acceptable goodness-of-fit indices and good reliability measures (α=0·77; ω=0·83). Intraclass correlation coefficient for the total score (0·82) and analysis of the Bland–Altman plot suggested good reproducibility of the scale.

The scale presents good evidence of validity and reliability. This innovative study created a useful tool for evaluation of the impact of the Dietary Guidelines for the Brazilian Population.

For dietary assessment, mobile devices with a camera can be used as an alternative to hand-written paper records. The Nutritional Tracking Information Smartphone (Nutris-Phone) study aimed to examine relative validity and feasibility of a photo-based dietary record in everyday life.

Parallel to the photo-based technique, a weighed record was performed. Participant satisfaction was assessed by questionnaire. A trained nutrition scientist evaluated portion sizes and nutrient content was calculated (DGExpert). Spearman correlation and Bland–Altman analyses were applied.

Healthy, non-pregnant volunteers (≥18 years) without intent to lose weight recruited at Ulm University, Germany.

Sixty-six participants (36 % males, median age 22·0 (interquartile range 20·0–25·0) years) took pictures of foods and beverages consumed with a commercially available mobile phone.

Significant correlation between the photo-based and weighed record was observed: energy (r=0·991), carbohydrate (r=0·980), fat (r=0·972), protein (r=0·988), fibre (r=0·941). Bland–Altman analyses indicated comparable means and acceptable 95 % limits of agreement (energy: −345·2 to 302·9 kJ (−82·5 to 72·4 kcal); carbohydrate: −15·2 to 13·1 g; fat: −6·4 to 6·4 g; protein: −5·9 to 5·6 g; fibre: −2·7 to 2·5 g). However, with increasing intake level, underestimation by the digital method was present (except for fat, all P<0·01). Over 80 % of participants were satisfied with the photo-based record. In nearly 90 %, technical implementation was without major problems.

Compared with a weighed record, the photo-based dietary record seems to be valid, feasible and user-friendly to estimate energy, macronutrient and fibre intakes, although a systematic bias with increasing levels of intake should be kept in mind.

The majority of groceries purchased by US households are industrially processed, yet it is unclear how processing level influences diet quality. We sought to determine if processing level is associated with diet quality of grocery purchases.

We analysed grocery purchasing data from the National Household Food Acquisition and Purchase Survey 2012–2013. Household grocery purchases were categorized by the NOVA framework as minimally processed, processed culinary ingredients, processed foods or ultra-processed foods. The energy share of each processing level (percentage of energy; %E) and Healthy Eating Index-2015 (HEI-2015) component and total scores were calculated for each household’s purchases. The association between %E from processed foods and ultra-processed foods, respectively, and HEI-2015 total score was determined by multivariable linear regression. Foods purchased by households with the highest v. lowest ultra-processed food purchases and HEI-2015 total score <40 v. ≥60 were compared using linear regression.

USA.

Nationally representative sample of 3961 households.

Processed foods and ultra-processed foods provided 9·2 (se 0·3) % and 55·8 (se 0·6) % of purchased energy, respectively. Mean HEI-2015 score was 54·7 (se 0·4). Substituting 10 %E from minimally processed foods and processed culinary ingredients for ultra-processed foods decreased total HEI-2015 score by 1·8 points (β = −1·8; 95 % CI −2·0, −1·5). Processed food purchases were not associated with diet quality. Among households with high ultra-processed food purchases, those with HEI-2015 score <40 purchased less minimally processed plant-foods than households with HEI-2015 score ≥60.

Increasing purchases of minimally processed foods, decreasing purchases of ultra-processed foods and selecting healthier foods at each processing level may improve diet quality.

A wide variety of methods are available to assess dietary intake, each one with different strengths and weaknesses. Researchers face multiple challenges when diet and nutrition need to be accurately assessed, particularly in the selection of the most appropriate dietary assessment method for their study. The goal of the current collaborative work is to present a collection of available resources for dietary assessment implementation.

As a follow-up to the 9th International Conference on Diet and Physical Activity Methods held in 2015, developers of dietary assessment toolkits agreed to collaborate in the preparation of the present paper, which provides an overview of each toolkit. The toolkits presented include: the Diet, Anthropometry and Physical Activity Measurement Toolkit (DAPA; UK); the National Cancer Institute’s (NCI) Dietary Assessment Primer (USA); the Nutritools website (UK); the Australasian Child and Adolescent Obesity Research Network (ACAORN) method selector (Australia); and the Danone Dietary Assessment Toolkit (DanoneDAT; France). An at-a-glance summary of features and comparison of the toolkits is provided.

The present review contains general background on dietary assessment, along with a summary of each of the included toolkits, a feature comparison table and direct links to each toolkit, all of which are freely available online.

This overview of dietary assessment toolkits provides comprehensive information to aid users in the selection and implementation of the most appropriate dietary assessment method, or combination of methods, with the goal of collecting the highest-quality dietary data possible.

To assess the strength of correlation and agreement between mid-upper arm circumference (MUAC) and BMI, and determine suitable MUAC cut-offs, to detect wasting and severe wasting among non-pregnant adult women in India.

Cross-sectional studies were conducted in five high-burden pockets of four Indian states.

Prevalence of malnutrition among women and children is very high in these pockets and the government plans to implement community-based pilot projects to address malnutrition in these areas.

Anthropometric measurements were carried out on 1716 women with children <5 years of age. However, analyses were conducted on 1538 non-pregnant adult women.

The results showed a strong correlation between MUAC and BMI in the non-pregnant women, with correlation coefficient of 0·860 (95 % CI 0·831, 0·883; P < 0·001). Cohen’s κ of 0·812 and 0·884 also showed good agreement between MUAC and BMI in identifying maternal wasting and severe wasting, respectively. The univariate regression model between MUAC and BMI explained 0·734 or 73 % of the variation in BMI. The MUAC cut-offs for wasting (BMI < 18·5 kg/m2) and severe wasting (BMI < 16·0 kg/m2) were calculated as 232 and 214·5 mm, respectively.

MUAC is a strong predictor of maternal BMI among non-pregnant women with children <5 years in high-burden pockets of four Indian states. In a resource-constrained setting where BMI may not be feasible, the MUAC cut-offs could reliably be used to screen wasting and severe wasting in non-pregnant women for providing appropriate care.

To illustrate the impact of combining 24 h recall (24hR) and FFQ estimates using regression calibration (RC) and enhanced regression calibration (ERC) on diet–disease associations.

Wageningen area, the Netherlands, 2011–2013.

Five approaches for obtaining self-reported dietary intake estimates of protein and K were compared: (i) uncorrected FFQ intakes (FFQ); (ii) uncorrected average of two 24hR ( $\overline {\rm R}$ ); (iii) average of FFQ and $\overline {\rm R}$ ( ${\overline {\rm F}}\,\overline {\rm R}}$ ); (iv) RC from regression of 24hR v. FFQ; and (v) ERC by adding individual random effects to the RC approach. Empirical attenuation factors (AF) were derived by regression of urinary biomarker measurements v. the resulting intake estimates.

Data of 236 individuals collected within the National Dietary Assessment Reference Database.

Both FFQ and 24hR dietary intake estimates were measured with substantial error. Using statistical techniques to correct for measurement error (i.e. RC and ERC) reduced bias in diet–disease associations as indicated by their AF approaching 1 (RC 1·14, ERC 0·95 for protein; RC 1·28, ERC 1·34 for K). The larger sd and narrower 95% CI of AF obtained with ERC compared with RC indicated that using ERC has more power than using RC. However, the difference in AF between RC and ERC was not statistically significant, indicating no significantly better de-attenuation by using ERC compared with RC. AF larger than 1, observed for the ERC for K, indicated possible overcorrection.

Our study highlights the potential of combining FFQ and 24hR data. Using RC and ERC resulted in less biased associations for protein and K.

To examine relationships between frequency of adolescents eating alone (dependent variable) and diet, weight status and perceived food-related parenting practices (independent variables).

Analyses of publicly available, cross-sectional, web-based survey data from adolescents.

Online consumer opinion panel.

A US nationwide sample of adolescents (12–17 years) completed Family Life, Activity, Sun, Health, and Eating (FLASHE) Study surveys to report demographic and family meal characteristics, weight, dietary intake, home food availability and perceptions of parenting practices. Parents provided information about demographic characteristics. Logistic regression analyses were used to test for associations between variables.

About 20 % of adolescents reported often eating alone (n 343) v. not often eating alone (n 1309). Adjusted odds of adolescents often eating alone were significantly higher for non-Hispanic Black compared with non-Hispanic White adolescents (OR=1·7) and for overweight or obese compared with normal- or underweight adolescents (OR=1·6). Adjusted odds of adolescents eating alone were significantly lower for those who reported that fruits and vegetables were often/always available in the home (OR=0·65), for those who perceived that parents had expectations about fruit and vegetable intake (OR=0·71) and for those who agreed with parental authority to make rules about intake of junk food/sugary drinks (OR=0·71). Junk food and sugary drink daily intake frequency was positively associated with often eating alone.

Often eating alone was related to being overweight/obese, having less healthy dietary intake and perceptions of less supportive food-related parenting practices.

Dietary questionnaires for assessing dietary intakes among populations of individuals aged 80 years or older (the very old) are very limited. We examined the relative validity of forty-three nutrients and twenty-seven food groups estimated by a brief-type self-administered diet history questionnaire (BDHQ) targeting very old Japanese, using semi-weighed dietary records (DR) as a reference.

Between June and August 2012 and between June 2015 and February 2016, a three-day non-consecutive DR (at two-week intervals) and a BDHQ were completed.

Tokyo, the capital prefecture of Japan.

Eighty very old Japanese (thirty-six men and forty-four women) aged 82–94 years.

The median intakes of 40–70 % of the crude and energy-adjusted nutrients estimated by the BDHQ were significantly different from those estimated by the DR. The median Spearman’s correlation coefficient of nutrient intakes between the BDHQ and the DR was 0·39–0·46. About half (48–56 %) of the food groups were significantly different in terms of the median intakes estimated by the BDHQ and the DR in crude and energy-adjusted values. The median Spearman’s correlation coefficient between the BDHQ and the DR was 0·45–0·48.

Acceptable Spearman’s correlations (≥0·3) were obtained for many dietary intakes among the very old Japanese population. The BDHQ is a good candidate for epidemiological studies among very old Japanese, although, for some nutrients and food groups, the difficulty of estimating accurate median intakes is one of the limitations for the tool. Further efforts to enhance the validity of the BDHQ for very old populations are needed.

The present study aimed to take stock of nutrition interventions that warrant consideration as a minimum package of interventions in Indonesia to improve four key nutrition indicators for adolescents: stunting, thinness, overweight and anaemia.

We conducted a review of the peer-reviewed literature published between 1995 and 2017 on nutrition-specific and nutrition-sensitive interventions that target adolescents in Indonesia. The search to identify studies was conducted in PubMed, Google Scholar and EMBASE, using key search terms. We also explored programmatic and policy documents from the grey literature as they related to adolescents and/or Indonesia. Our search yielded thirty-five peer-reviewed articles and programmatic documents.

Indonesia.

Adolescent girls and boys.

There is very limited evidence on the impact of interventions specifically among adolescents in Indonesia. Nevertheless, findings from our review suggest the minimum package of interventions in Indonesia could include the following nutrition-specifc interventions: (i) iron–folic acid supplements, paired with antihelminths delivered at scale via school-based platforms and through health centres; and (ii) diet counselling and nutrition education provided through school-based platforms, adolescent youth centres/peer education and technology-based platforms. The minimum package could also include the following nutrition-sensitive interventions: (i) improving access to reproductive health services; and (ii) increasing the coverage of interventions designed to increase school attendance.

Programmes and policies targeting adolescent nutrition are relatively new and coverage is low. To improve the nutritional status of this vulnerable population, additional evaluations of adolescent programming and surveillance data on adolescents are needed.

To describe the relationship between adherence to distinct dietary patterns and nutrition literacy.

We identified distinct dietary patterns using principal covariates regression (PCovR) and principal components analysis (PCA) from the Diet History Questionnaire II. Nutrition literacy was assessed using the Nutrition Literacy Assessment Instrument (NLit). Cross-sectional relationships between dietary pattern adherence and global and domain-specific NLit scores were tested by multiple linear regression. Mean differences in diet pattern adherence among three predefined nutrition literacy performance categories were tested by ANOVA.

Metropolitan Kansas City, USA.

Adults (n 386) with at least one of four diet-related diseases.

Three diet patterns of interest were derived: a PCovR prudent pattern and PCA-derived Western and Mediterranean patterns. After controlling for age, sex, BMI, race, household income, education level and diabetes status, PCovR prudent pattern adherence positively related to global NLit score (P < 0·001, β = 0·36), indicating more intake of prudent diet foods with improved nutrition literacy. Validating the PCovR findings, PCA Western pattern adherence inversely related to global NLit (P = 0·003, β = −0·13) while PCA Mediterranean pattern positively related to global NLit (P = 0·02, β = 0·12). Using predefined cut points, those with poor nutrition literacy consumed more foods associated with the Western diet (fried foods, sugar-sweetened beverages, red meat, processed foods) while those with good nutrition literacy consumed more foods associated with prudent and Mediterranean diets (vegetables, olive oil, nuts).

Nutrition literacy predicted adherence to healthy/unhealthy diet patterns. These findings warrant future research to determine if improving nutrition literacy effectively improves eating patterns.

To validate digitally displayed photographic portion-size estimation aids (PSEA) against a weighed meal record and compare findings with an atlas of printed photographic PSEA and actual prepared-food PSEA in a low-income country.

Participants served themselves water and five prepared foods, which were weighed separately before the meal and again after the meal to measure any leftovers. Participants returned the following day and completed a meal recall. They estimated the quantities of foods consumed three times using the different PSEA in a randomized order.

Two urban and two rural communities in southern Malawi.

Women (n 300) aged 18–45 years, equally divided by urban/rural residence and years of education (≤4 years and ≥5 years).

Responses for digital and printed PSEA were highly correlated (>91 % agreement for all foods, Cohen’s κw = 0·78–0·93). Overall, at the individual level, digital and actual-food PSEA had a similar level of agreement with the weighed meal record. At the group level, the proportion of participants who estimated within 20 % of the weighed grams of food consumed ranged by type of food from 30 to 45 % for digital PSEA and 40–56 % for actual-food PSEA. Digital PSEA consistently underestimated grams and nutrients across foods, whereas actual-food PSEA provided a mix of under- and overestimates that balanced each other to produce accurate mean energy and nutrient intake estimates. Results did not differ by urban and rural location or participant education level.

Digital PSEA require further testing in low-income settings to improve accuracy of estimations.

The Composite Index of Anthropometric Failure (CIAF) can only be applied to children under 5 years of age and does not contemplate obesity. The aim of this study was to propose an Extended CIAF (ECIAF) that combines the characterization of malnutrition due to undernutrition and excess weight, and apply it in six Argentine provinces.

ECIAF excludes children not in anthropometric failure (group A) and was calculated from a percentage of children included in malnutrition categories B: wasting only; C: wasting and underweight; D: wasting, stunting and underweight; E: stunting and underweight; F: stunting only; Y: underweight only; G: only weight excess; and H: stunting and weight excess.

Cross-sectional study conducted in Buenos Aires, Catamarca, Chubut, Jujuy, Mendoza and Misiones (Argentina).

10 879 children of both sexes aged between 3 and 13·99.

ECIAF in preschool children (3 to 4·99 years) was 15·1 %. The highest prevalence was registered in Mendoza (16·7 %) and the lowest in Misiones (12·0 %). In school children (5 to 13·99 years) ECIAF was 28·6 %. Mendoza also recorded the highest rate (30·7 %), while Catamarca and Chubut had the lowest values (27·0 %). In the whole sample, about 25 % of the malnutrition was caused by undernutrition and 75 % by excess weight.

The ECIAF summarizes anthropometric failure by both deficiency and excess weight and it highlights that a quarter of the malnutrition in the Argentine population was caused by undernutrition, although there are differences between Provinces (P < 0·05). ECIAF estimates are higher than those of CIAF or under-nutrition.

To analyse the Nutritional Knowledge Test (NKT) using Item Response Theory (ITR) analysis and to assess the construct validity of the Nutritional Knowledge Scale (NKTS) and its associations with adolescent food group consumption and nutritional biomarkers.

Cross-sectional study.

Multicentre investigation conducted in ten European cities.

Adolescents aged 12·5–17·5 years (n 3215) who completed over 75 % of the NKT.

Factor analysis indicated that the NKT can be analysed with a one-dimensional model. Eleven out of twenty-three items from the NKT presented adequate parameters and were selected to be included in the NKTS. Nutrition knowledge was positively associated with consumption of fruits, cereals, dairy products, pulses, meat and eggs, and fish, as well as with blood concentrations of vitamin C, β-carotene, n-3 fatty acids, holo-transcobalamin, cobalamin and folate; nutrition knowledge was negatively associated with intake of olives and avocado, alcohol and savoury snacks.

The NKTS assessed nutritional knowledge adequately and it is proposed as a new tool to investigate this subject in future studies.

To characterize the association of longitudinal changes in maternal anthropometric measures with neonatal anthropometry and to assess to what extent late-gestational changes in maternal anthropometry are associated with neonatal body composition.

In a prospective cohort of pregnant women, maternal anthropometry was measured at six study visits across pregnancy and after birth, neonates were measured and fat and lean mass calculated. We estimated maternal anthropometric trajectories and separately assessed rate of change in the second (15–28 weeks) and third trimester (28–39 weeks) in relation to neonatal anthropometry. We investigated the extent to which tertiles of third-trimester maternal anthropometry change were associated with neonatal outcomes.

Women were recruited from twelve US sites (2009–2013).

Non-obese women with singleton pregnancies (n 2334).

A higher rate of increase in gestational weight gain was associated with larger-birth-weight infants with greater lean and fat mass. In contrast, higher rates of increase in maternal anthropometry measures were not associated with infant birth weight but were associated with decreased neonatal lean mass. In the third trimester, women in the tertile of lowest change in triceps skinfold (−0·57 to −0·06 mm per week) had neonates with 35·8 g more lean mass than neonates of mothers in the middle tertile of rate of change (−0·05 to 0·06 mm per week).

The rate of change in third-trimester maternal anthropometry measures may be related to neonatal lean and fat mass yet have a negligible impact on infant birth weight, indicating that neonatal anthropometry may provide additional information over birth weight alone.

To use cognitive interviewing and pilot testing to develop a survey instrument feasible for administering in the food pantry setting to assess daily intake frequency from several major food groups and dietary correlates (e.g. fruit and vegetable barriers) – the FRESH Foods Survey.

New and existing survey items were adapted and refined following cognitive interviews. After piloting the survey with food pantry users in the USA, preliminary psychometric and construct validity analyses were performed.

Three US food banks and accompanying food pantries in Atlanta, GA, San Diego, CA, and Buffalo, NY.

Food pantry clients (n 246), mostly female (68 %), mean age 54·5 (sd 14·7) years.

Measures of dietary correlates performed well psychometrically: Cronbach’s α range 0·71–0·90, slope (α) parameter range 1·26–6·36, and threshold parameters (β) indicated variability in the ‘difficulty’ of the items. Additionally, all scales had only one eigenvalue above 1·0 (range 2·07–4·71), indicating unidimensionality. Average (median, Q1–Q3) daily intakes (times/d) across six dietary groups were: fruits and vegetables (2·87, 1·87–4·58); junk foods (1·16, 0·58–2·16); fast foods and similar entrées (1·45, 0·58–2·03); whole-grain foods (0·87, 0·58–1·71); sugar-sweetened beverages (0·58, 0·29–1·29); milk and milk alternatives (0·71, 0·29–1·29). Significant correlations between dietary groups and dietary correlates were largely in the directions expected based on the literature, giving initial indication of convergent and discriminant validity.

The FRESH Foods Survey is efficient, tailored to food pantry populations, can be used to monitor dietary behaviours and may be useful to measure intervention impact.

To identify differences in dietary quality, dietary greenhouse gas (GHG) emissions and food consumption over 20 years in a Dutch cohort.

Participants (n 8932) filled out an FFQ in 1993–1997 and in 2015. The Dutch Healthy Diet index 2015 (DHD15-index) score, GHG emissions and consumption of food groups (g/4184 kJ (1000 kcal)) were compared between the time points with paired t tests.

The Netherlands.

European Prospective Investigation into Cancer and Nutrition – Netherlands (EPIC-NL) cohort, aged 18–65 years at baseline.

Total energy intake decreased by –678 (95 % CI –4908, 3377) kJ/d (–162 (95 % CI –1173, 807) kcal/d) for men and –372 (95 % CI –3820, 3130) kJ/d (–89 (95 % CI –913, 748) kcal/d) for women. DHD15-index scores increased by 11 % (from 64·8 to 71·9 points) and 13 % (from 65·2 to 73·6 points) in men and women, respectively (P < 0·0001), mainly due to an increased (shell)fish and nuts/seeds/nut paste consumption. After energy intake adjustment, dietary-related GHG emissions increased by 5 % in men (2·48–2·61 kg CO2-eq/4184 kJ (1000 kcal), P < 0·0001) and were similar in women (0·4 %, 2·70–2·71 kg CO2-eq/4184 kJ (1000 kcal), P = 0·3930) due to the increased consumption of (shell)fish, nuts/seeds/nut paste, poultry and higher GHG-intensive red meats such as beef.

This Dutch cohort analyses showed more healthy diets without mitigated GHG emissions over a 20-year period, at similar energy intakes. Higher consumption of (shell)fish and poultry was not yet at the expense of red and processed meat. Lower consumption of animal-based foods is needed to achieve healthier as well as environmentally friendly diets.