Childbirth is a major life-changing event, this period is an opportunity to improve eating habits. The aim of this longitudinal study was to identify and characterise dietary changes in women according to their parity status. Dietary intake data from 4194 women of childbearing age included in the NutriNet-Santé cohort were derived using a FFQ, administered in 2014 and 2018, distinguishing between organic and conventional food consumption. Women were classified into four groups: ‘previous children’, ‘multiparous’, ‘primiparous’ and ‘nulliparous’. Multi-adjusted ANCOVA models were used to estimate the changes according to the parity group. Changes in food consumption towards a more plant-based, healthier and organic diet were observed in all four groups of women, although to various degrees. In multivariable models, ‘Nulliparous’ women showed a greater improvement in terms of ‘sustainable’ food consumption than ‘previous children’ women. ‘Primiparous’ women significantly increased their energy intake (+349 (269–429) kcal/d) and their consumption of dairy products (+30 (3–56) g/d), and they significantly decreased their consumption of alcohol (–23 (–32–15) g/d), coffee and tea (–107 (–155–60) g/d). Regarding organic food, ‘nulliparous’ women increased their consumption more than ‘previous children’ and ‘primiparous’ women were those who were most frequently in the top quintile of organic food increase. Although there were dietary changes in all groups of women according to their parity, childless women have a shift moving towards a more sustainable diet. Women who had a first child reduced their alcohol and caffeine consumption.

The overall aim of precision nutrition is to replace the ‘one size fits all’ approach to dietary advice with recommendations that are more specific to the individual in order to improve the prevention or management of chronic disease. Interest in precision nutrition has grown with advancements in technologies such as genomics, proteomics, metabolomics and measurement of the gut microbiome. Precision nutrition initiatives have three major applications in precision medicine. First, they aim to provide more ‘precision’ dietary assessments through artificial intelligence, wearable devices or by employing omic technologies to characterise diet more precisely. Secondly, precision nutrition allows us to understand the underlying mechanisms of how diet influences disease risk and identify individuals who are more susceptible to disease due to gene–diet or microbiota–diet interactions. Third, precision nutrition can be used for ‘personalised nutrition’ advice where machine-learning algorithms can integrate data from omic profiles with other personal and clinical measures to improve disease risk. Proteomics and metabolomics especially provide the ability to discover new biomarkers of food or nutrient intake, proteomic or metabolomic signatures of diet and disease, and discover potential mechanisms of diet–disease interactions. Although there are several challenges that must be overcome to improve the reproducibility, cost-effectiveness and efficacy of these approaches, precision nutrition methodologies have great potential for nutrition research and clinical application.

Dietary patterns (DP) rich in plant foods are associated with improved health and reduced non-communicable disease risk. In October 2021, the Nutrition Society hosted a member-led conference, held online over 2 half days, exploring the latest research findings examining plant-rich DP and health. The aim of the present paper is to summarise the content of the conference and synopses of the individual speaker presentations are included. Topics included epidemiological analysis of plant-rich DP and health outcomes, the effects of dietary interventions which have increased fruit and vegetable (FV) intake on a range of health outcomes, how adherence to plant-rich DP is assessed, the use of biomarkers to assess FV intake and a consideration of how modifying behaviour towards increased FV intake could impact environmental outcomes, planetary health and food systems. In conclusion, although there are still considerable uncertainties which require further research, which were considered as part of the conference and are summarised in this review, adopting a plant-rich DP at a population level could have a considerable impact on diet and health outcomes, as well as planetary health.

No studies have investigated the associations between established plant-based diet indices and the metabolic syndrome (MetS). We evaluated the associations between an overall plant-based diet index (PDI), healthy PDI (hPDI), unhealthy PDI (uPDI) and the MetS in a nationally representative sample using data from 14 450 Korean adults (≥19 years) in the Korea National Health and Nutrition Examination Survey 2012–2016. Dietary intakes were assessed by a semi-quantitative FFQ. In the PDI, all plant foods received positive scores. In the hPDI, only healthy plant foods received positive scores. In the uPDI, only unhealthy plant foods received positive scores. All indices reverse scored animal food intake. Multivariable logistic regression models were used to examine the associations between three PDI and the MetS by sex, adjusting for potential risk factors. A total of 23·3 % of Korean adults had the MetS. In the overall study population, individuals in the highest quintile of uPDI had greater odds (OR 1·54, 95 % CI 1·28, 1·86, Ptrend < 0·001) of the MetS than those in the lowest quintile. Higher uPDI score was associated with higher odds of hypertriacylglycerolaemia in men and abdominal obesity, high fasting glucose and hypertriacylglycerolaemia in women. No significant associations were observed between PDI, hPDI and the MetS. Greater adherence to unhealthy plant-based diets was associated with greater odds of the MetS and its components suggesting the importance of the quality of plant-based diet in South Korean adults. Sex differences may be considered when recommending plant-based diets for the prevention and management of metabolic diseases.

Few studies have evaluated the association between a healthful plant-based diet and health-related quality of life (HRQoL). We followed 50 290 women in the Nurses’ Health Study (NHS; 1992–2000) and 51 784 women in NHSII (1993–2001) for 8 years to investigate changes in plant-based diet quality in relation to changes in physical and mental HRQoL. Plant-based diet quality was assessed by three plant-based diet indices: overall plant-based diet index (PDI), healthful PDI (hPDI) and unhealthful PDI (uPDI). Physical and mental HRQoL were measured by physical component score (PCS) and mental component score (MCS) of the 36-Item Short Form Health Survey. Diet was assessed 2 years before the HRQoL measurements and both were updated every 4 years. The associations between 4-year changes in PDIs and HRQoL were evaluated. Each 10-point increase in PDI was associated with an improvement of 0·07 (95 % CI 0·01, 0·13) in PCS and 0·11 (95 % CI 0·05, 0·16) in MCS. A 10-point increase in hPDI was associated with an increment of 0·13 (95 % CI 0·08, 0·19) in PCS and 0·09 (95 % CI 0·03, 0·15) in MCS. Conversely, a 10-point increase in uPDI was associated with decreases in PCS and MCS (−0·07 (95 % CI −0·12, −0·02) and −0·10 (95 % CI −0·16, −0·05), respectively). Compared with a stable diet, an increase in hPDI was significantly associated with improvements in physical HRQoL in older women and with mental HRQoL in younger women. In conclusion, adherence to a healthful plant-based diet was modestly associated with improvements in both physical and mental dimensions of HRQoL.

Diabetes is a common chronic disease with various complications. The present study was conducted to determine the association of plant-based diet index (PDI) and dietary acid load (DAL) with sleep status as well as mental health in type 2 diabetic women. In this cross-sectional study, a validated FFQ was used to assess dietary intakes of 230 diabetic patients. We created a whole PDI, healthful PDI (hPDI) and unhealthful PDI (uPDI). DAL was calculated based on potential renal acid load and net endogenous acid production method. The Pittsburgh Sleep Quality Index and twenty-one-item Depression, Anxiety and Stress Scale were used to assess sleep and mental health disorders, respectively. Participants in the top group of uPDI had greater risk of poor sleep (OR 6·47, 95 % CI 2·75, 15·24). However, patients who were in the top group of hPDI had a lower risk of sleep problems (OR 0·28, 95 % CI 0·13, 0·62). Participants in the top group of uPDI had greater risk of depression, anxiety and stress (OR 9·35, 95 % CI 3·96, 22·07; OR 4·74, 95 % CI 2·28, 9·85; OR 4·24, 95 % CI 2·14, 8·38, respectively). In conclusion, participants with higher DAL scores and patients who adhered to animal-based diets rather than plant-based diets were more likely to be poor sleepers and have mental health disorders.