A growing standardisation of eating behaviours worldwide is observed, especially in children, notably characterised by the increasing consumption of both unsustainable animal- and plant-based ultra-processed foods (UPFs). The objective of this study was to identify five high-impact eating behaviours (HIBs) in a French child population (living in Clermont-Ferrand city and surroundings, n = 92, aged 6–15), that is, behaviours to change for the strongest positive impact on health and sustainability. For this, both multidisciplinary top-down and participatory bottom-up approaches has been carried out. First, from European and French dietary guidelines, desk research, European researchers’ evaluation, and expert interviews and workshops the technical potential (for their impact on health and environment), plasticity and feasibility of 40 HIB were first quantified (top-down approach). Secondly, in the French living lab (LL), from photo-voice and focus groups with children, online surveys, meetings with families and children, interviews with stakeholders, and assessments of the behavioural change potential of the French LL children’s target, five HIB were finally selected (bottom-up approach). Therefore, among the initial 342 European recommended eating behaviours, the selected HIBs for our specific population were: limiting the consumption of UPFs (notably those high in added salt, sugars and/or fats), eating 0–3 servings of meat/week, eating three servings of legumes/week, choosing primarily wholegrain than refined cereals, and choose water instead of sweetened beverages. These five HIBs constitutes a solid basis to perform next LL participatory actions, notably to test HIB feasibility/plasticity, and implement them in real life conditions through transversal actions with non-researcher.

Eating duration and shift work can both influence metabolic regulation, but their joint associations with diabetes are unknown. We aimed to examine the independent and joint associations of eating duration and shift work with diabetes in a cross-sectional study using a nationally representative sample of US workers. We included 14852 eligible participants from the National Health and Nutrition Examination Survey, 2005–2010 and 2017–2020. Eating duration was calculated based on first and last eating occasions from 24-h dietary recalls. Long eating duration (LED: ≥ 13 h) v. short eating duration (SED: < 13 h) was defined based on the median. Workers were classified as engaging in shift work (SW, n 5140) v. non-shift work (NSW, n 8945) based on self-report. Logistic regressions were used to examine the associations of LED and SW with diabetes, independently and jointly with stratification by age. LED was associated with higher odds of diabetes among workers aged < 45 years (OR, 1·51; 95 % CI, 1·05–2·19) but not among workers aged ≥ 45 years (OR, 0·98; 95 % CI, 0·79–1·20). SW was associated with higher odds of diabetes among both younger (OR, 1·28; 95 % CI, 0·88–1·85) and older workers (OR, 1·28; 95 % CI, 1·04–1·58). There was suggestive evidence that workers with both LED and SW had higher odds of diabetes compared with those with SED and NSW, but the association was stronger among younger (OR, 1·40; 95 % CI, 0·85–2·28) than older workers (OR, 1·28; 95 % CI, 0·99–1·66). LED and SW were independently associated with increased odds of diabetes with suggestive evidence on their joint associations, but associations varied by workers’ age.

This study aimed to develop and validate a questionnaire that investigates sugar-related eating behaviour, excessive consumption, and addictive-like eating. This questionnaire was validated using a rigorous process assessing content validity, face validity, reliability testing, feasibility testing, and construct validity. Spearman’s correlation coefficients and Cronbach’s alpha were used to assess reliability. Feasibility testing was used to further validate and confirm the scoring/categorisation of ‘low’, ‘medium’, and ‘high’ scorers for use in future research. Exploratory factor analysis and reliability analysis were used to determine underlying latent factors and assess construct validity. Content validity was assessed by health professionals (n = 16), face validity was assessed by the lay public who had no expertise in nutrition or addiction (n = 20). Reliability (n = 54), repeat reliability (n = 50), and feasibility (n = 113) testing were assessed with a sample from the lay public. Spearman’s correlation coefficients were in the range of 0.58–0.91 and were statistically significant (P < 0.001), indicating good temporal stability within the questionnaire. Cronbach’s alpha coefficients were in the range of 0.62–0.93, indicating good internal consistency. Feasibility testing confirmed the use of calculating an ‘average total score’ from the data set and splitting the data set into tertiles: low, medium, and high scorers. Exploratory factor analysis confirmed three latent factors: F1: Compulsive Eating; F2: Comfort Eating; and F3: Withdrawal. Results suggest the questionnaire is highly reliable and was successfully validated. This questionnaire can be used in research to investigate problematic and addictive-like eating behaviour and its effects on ill health.

Flexitarian, vegetarian and vegan diets are increasingly popular, particularly amongst young adults. This is the first randomised dietary intervention to investigate the health, wellbeing, and behavioural implications of consuming a basal vegetarian diet that additionally includes low-to-moderate amounts of red meat compared to one containing plant-based meat alternatives (PBMAs) in young adults (NCT04869163)(1). The objective for the current analysis is to measure adherence to the intervention, nutrition behaviours, and participants’ experience with their allocated dietary group. Eighty healthy young adults participated in this 10-week dietary intervention as household pairs. Household pairs were randomised to receive approximately three serves of beef and lamb meat (average of 390 g total cooked weight per person per week, flexitarian group) or PBMAs (350–400 g, vegetarian group) on top of a basal vegetarian diet. Participants were supported to adopt healthy eating behaviours, and this intervention was developed and implemented using a behaviour change framework(2). Diet adherence (eating allocated meat or PBMA, abstaining from animal-based foods not provided by researchers) was monitored daily, with total scores calculated at the end of the 10-week intervention period. Eating experiences were measured by the Positive Eating Scale and a purpose-designed exit survey, and a food frequency questionnaire measured dietary intake. Analyses used mixed effects modelling taking household clustering into account. The average total adherence score was 91.5 (SD = 9.0) out of a possible 100, with participants in the flexitarian group scoring higher (96.1, SD = 4.6, compared to 86.7, SD = 10.0; p < 0.001). Those receiving meat were generally more satisfied with this allocation compared to those receiving the PBMAs, even though a leading motivation for participants joining the study was an opportunity to try plant-based eating (35% expressed that that interest). Participants in both intervention groups had increased vegetable intake (p < 0.001), and reported more positive eating experiences (p = 0.020) and satisfaction with eating (p = 0.021) at the end of the 10-week intervention relative to baseline values. Behavioural methods to encourage engagement with the trial were successful, as participants demonstrated excellent adherence to the intervention. The flexitarian and vegetarian diets elicited different responses in adherence and eating experience. This holds relevance for the inclusion of red meat and PBMAs in healthy, sustainable dietary patterns beyond this study alone.

Rapid prenatal and postnatal weight gain seem to alter appetite regulation and hypothalamic functions through different pathways; however, little is known on how early life growth trajectories may influence appetitive traits in school-age. We aimed to explore the associations between weight trajectories from birth to 5 years and appetitive traits at 7. Participants were from the Generation XXI birth cohort (n 3855). Four weight trajectories were investigated: ‘normal weight gain’ (closely overlaps the 50th percentile in the weight-for-age curve), ‘weight gain during infancy’ (low birth weight and weight gain mainly during infancy), ‘weight gain during childhood’ (continuous weight gain since birth) and ‘persistent weight gain’ (always showing higher weight than the average). Appetitive traits were assessed through the Children’s Eating Behaviour Questionnaire. Associations were tested using generalised linear models, adjusted for maternal and child characteristics. Compared with ‘normal weight gain’, those in the other growth trajectories showed greater enjoyment of food and eating in response to food stimuli (i.e. Food Responsiveness) but were less able to compensate for prior food intake and ate faster at 7 (i.e. less Satiety Responsiveness and Slowness in Eating). Also, those with ‘weight gain during infancy’ showed to have greater Emotional Overeating and less Emotional Undereating and were fussier. Associations were stronger if greater weight gain occurred during infancy. Early infancy seems to be a sensitive period in the development of later appetitive traits. The control of rapid growth during infancy, besides strategies focused on the overall environment where children are living, is necessary.

Experiencing a change in partnership status at older ages might have detrimental effects on an individual's habits, including eating behaviours. Prior studies presented evidence that widowhood is related to altered diets with a decrease in the amount of protein consumed, which is considered to be an important risk factor of frailty among older people. Using data from Waves 4–8 of the Survey of Health, Ageing and Retirement in Europe (N = 134,313), we investigate the association between stability and changes in partnership status and changes in the frequency of protein consumption at older ages. We also explore the potential moderating role played by changes in economic resources. Having never been married, being divorced and being widowed were significantly associated with a lower frequency of protein consumption among both men and women. The transition to widowhood was significantly associated with a reduction in the frequency of protein consumption, while this same association was not found in the transition to divorce. Subjective evaluation of economic resources did not moderate the relationship between changes in partnership status and frequency of protein consumption. In short, changes in eating behaviours after having experienced the loss of a partner due to widowhood might contribute to accounting for health differentials between those ageing alone and those with a partner.

This study aims to evaluate the interaction effect of socio-economic environment (SEE) in the relationship between the eating location (EL) and diet quality, in children and adolescents. Data included Portuguese children and adolescents (3–17 years) from a National Dietary Survey Sample (IAN-AF 2015/2016, n 987). Dietary intake was obtained by 2-d food diaries (children) or 2–24-h-recall (adolescents). Participants were classified into four groups of EL: ‘Home’, ‘Other homes’, ‘School’ and ‘Restaurants’. Diet quality was measured as a higher adherence to a healthy eating pattern. A previous developed socio-economic classification was used, and participants were grouped as belonging to a low socio-economic environment (LSE) or middle-high socio-economic environment (MHSE). Linear regression models were used to evaluate the association between EL and diet quality, stratified by the SEE. A statistically significant interaction effect was found (P < 0·01) for the SEE in the association between EL and diet quality. After adjustment for potential confounders, in LSE, participants belonging to ‘Other homes’ (β = –2·07; 95 % CI:–3·70, –0·44) and ‘Restaurants’ (β = –3·31; 95 % CI: –5·08, –1·54) had lower scores in the diet quality score, comparing to ‘Home’. In MHSE, comparing with ‘Home’, ‘Restaurants’ showed lower diet quality (β = –1·56; 95 % CI:–2·65, –0·48), while the ‘School’ had better diet quality (β = 0·90; 95 % CI: 0·16, 1·64). The SEE influences the association between EL and diet quality and, belonging to more disadvantaged SEE, might represent a higher risk of unhealthy eating habits when eating out-of-home.

Weight cycling is prevalent in sports/professions with body composition standards, and has been associated with weight management behaviours that may contribute to suboptimal diet quality and weight gain. US Army Soldiers may be at increased risk of weight cycling relative to civilians due to mandated body composition standards. However, the relationship between weight cycling, weight management behaviours, BMI and diet quality among Soldiers is unknown. In this cross-sectional study, 575 Soldiers (89 % enlisted, 90 % male, 23 ± 4 years) at Army installations at Joint Base Elmendorf-Richardson, AK, Joint-Base Lewis McChord, WA, and Fort Campbell, KY completed questionnaires on food frequency, health-related behaviours and history of weight cycling (≥ 3 weight fluctuations ≥ 5 % body weight). Weight cycling was reported by 33 % of Soldiers. Those who reported weight cycling reported higher BMI (27 ± 4 v. 25 ± 3 kg/m2, P < 0·001) and higher prevalence of engaging in weight management behaviours prior to body weight screening but did not report lower dietary quality (Healthy Eating Index-2015 (HEI) scores 59 ± 10 v 59 ± 11, P = 0·46) relative to those who did not report weight cycling. Results of mediation analyses suggested that weight cycling may affect BMI both directly (c’ = 1·19, 95 % CI: 0·62, 1·75) and indirectly (ab = 0·45, 95 % CI: 0·19, 0·75), and HEI scores indirectly (ab = 0·69, 95 % CI: 0·20, 1·35) through the adoption of weight management behaviours. Weight cycling is common in Soldiers and is associated with higher BMI and higher prevalence of engaging in weight management behaviours that mediate associations between weight cycling, BMI and diet quality.

Inadequate sleep and poor eating behaviours are associated with higher risk of childhood overweight and obesity. Less is known about the influence sleep has on eating behaviours and consequently body composition. Furthermore, whether associations differ in boys and girls has not been investigated extensively. We investigate associations between sleep, eating behaviours and body composition in cross-sectional analysis of 5-year-old children. Weight, height, BMI, mid upper arm circumference (MUAC), abdominal circumference (AC) and skinfold measurements were obtained. Maternal reported information on child’s eating behaviour and sleep habits were collected using validated questionnaires. Multiple linear regression examined associations between sleep, eating behaviours and body composition. Sleep duration was negatively associated with BMI, with 1-h greater sleep duration associated with 0·24 kg/m2 (B = 0·24, CI −0·42, −0·03, P = 0·026) lower BMI and 0·21 cm lower (B = –0·21, CI −0·41, −0·02, P = 0·035) MUAC. When stratified by sex, girls showed stronger inverse associations between sleep duration (h) and BMI (kg/m2) (B = –0·32; CI −0·60, −0·04, P = 0·024), MUAC (cm) (B = –0·29; CI −0·58, 0·000, P = 0·05) and AC (cm) (B = –1·10; CI −1·85, −0·21, P = 0·014) than boys. Positive associations for ‘Enjoys Food’ and ‘Food Responsiveness’ with BMI, MUAC and AC were observed in girls only. Inverse associations between sleep duration and ‘Emotional Undereating’ and ‘Food Fussiness’ were observed in both sexes, although stronger in boys. Sleep duration did not mediate the relationship between eating behaviours and BMI. Further exploration is required to understand how sleep impacts eating behaviours and consequently body composition and how sex influences this relationship.

The transition from childhood to adolescence is a sensitive period, triggering changes in health- and weight-related behaviours including eating habits which likely vary between girls and boys. We aimed to characterise the changes in the frequency of consumption of select sugary foods and drinks (‘sweet treats’) among 4237 Finnish girls and boys during a 2-year follow-up period. Additionally, we examined four subgroups: children whose weight or waist normalised as well as children whose weight or waist circumference increased during follow-up. An FFQ was completed at 11·1 (sd 0·9) and again at 13·4 (sd 1·1) years of age. A sum variable sweet treat index (STI, range 0–84) captured the weekly consumption frequencies of sweet treats. From baseline to follow-up, the mean STI decreased among girls from 7·1 (95 % CI 6·9, 7·3) to 6·0 (95 % CI 5·9, 6·2) (P < 0·001) and boys from 8·5 (95 % CI 8·3, 8·8) to 7·8 (95 % CI 7·6, 7·8) (P < 0·001), although both sexes increased their chocolate/sweets consumption: girls from 1·3 (95 % CI 1·3, 1·4) to 1·6 (95 % CI 1·5, 1·6) (P < 0·001) and boys from 1·4 (95 % CI 1·3, 1·4) to 1·6 (95 % CI 1·6, 1·7) (P < 0·001), and boys increased their soft drink consumption from 1·4 (95 % CI 1·3, 1·4) to 1·5 (95 % CI 1·4, 1·5) (P = 0·020). We found similar decreases in both the weight and waist subgroups. To conclude, the total frequency of consumption of sweet treats decreased during early adolescence. A similar trend across subgroups suggests that the frequency of consumption of sweet treats is unrelated to becoming overweight.

Few longitudinal studies have evaluated the association between eating and drinking habits and the risk of obesity. Therefore, we conducted a 5-year longitudinal big data analysis for evaluating various eating and drinking habits and the risk of obesity. We analysed individuals without obesity who received medical check-ups from 2008 to 2012 and 5 years later from the JMDC Health check-up database. The primary outcome was the incidence of obesity (BMI ≥ 25 kg/m2), and the secondary outcome was the incidence of abdominal obesity (waist circumference ≥ 85 cm for men and 90 cm for women). Age- and sex-adjusted, and multivariate logistic regression analyses were conducted. Of 123 182 individuals without obesity at baseline, the median age was 45 (interquartile range 40, 51) years and 76 965 (62·5 %) were men. After 5 years, 7133 (5·8 %) people developed obesity and 12 725 (10·3 %) people developed abdominal obesity. Among six eating and drinking habits, skipping breakfast was associated with a higher risk of obesity (OR 1·21; 99 % CI 1·10, 1·34). In contrast, occasional (OR 0·86; 99 % CI 0·78, 0·94) or daily (OR 0·79; 99 % CI 0·68, 0·91) drinking of alcoholic beverages was associated with a lower risk of obesity. According to the 5-year longitudinal data, eating and drinking habits such as mild to moderate alcohol consumption and avoiding skipping breakfast may result in better obesity prevention. However, excess alcohol consumption would be harmful and should be avoided.