Search Results (113)

Background: Assessing food and nutrient intake is an important yet challenging component of nutrition research, particularly in populations at higher risk for dietary underreporting. Objective: To evaluate the feasibility, acceptability, and preliminary measurement characteristics of augmenting interviewer-administered 24 h dietary recalls with a photo-based mobile food record application (mCC: my Circadian Clock). Design: This was a randomized cross-over feasibility study in which each participant completed two sets of three 24 h dietary recalls. One set consisted of standard interviewer-administered recalls, while the other incorporated dietary intake captured via the mCC app during the 24 h preceding the recall to guide the interview. Participants: Participants (n = 10) were adults aged 18–65 years with obesity (BMI > 30 kg/m²) and less than a college-level education, recruited from a general community setting. Main Outcome Measures: Primary feasibility outcomes included recall adherence, protocol completion, participant burden, and usability of the mobile application. Secondary and exploratory outcomes included average energy intake (kcal/day), number of food items and eating occasions reported, Healthy Eating Index (HEI)-2015 scores, and recall duration. Statistical Analyses: Descriptive statistics and paired t-tests were used to explore differences between methods; analyses were considered exploratory and hypothesis-generating. Results: All enrolled participants completed every scheduled recall, resulting in 100% adherence and protocol completion. Most participants (70%) rated the mCC app as easy or very easy to use, although 60% reported greater burden with the Augmented Recalls. Average energy intake was 274 kcal/day lower with the augmented method compared with Standard Recalls (95% CI: −597, 50; p = 0.09), with no clear differences observed in reported food items, eating occasions, HEI-2015 scores, or recall duration. Conclusions: Augmenting interviewer-administered 24 h dietary recalls with a photo-based mobile food record is feasible and acceptable in adults with obesity, though it did not demonstrate clear improvements in dietary intake capture in this small feasibility sample. These findings provide practical guidance for refining technology-assisted recall protocols and informing the design of future, adequately powered studies. Full article

Background/Objectives: Avocados are nutrient-dense fruits rich in monounsaturated fats, fiber, and key micronutrients. Although avocado purchases increased in recent years, comprehensive national data on consumption patterns remains limited. Thus, this study aimed to characterize the prevalence, quantity, and context of avocado intake among the US population and to evaluate its contribution to daily nutrient intake. Methods: Day 1 24-h dietary recall data were analyzed from 19,086 participants aged ≥1 year in NHANES 2017–March 2020 and August 2021–August 2023. Avocado intake was identified using consumption data coded as avocado, avocado for use on a sandwich, guacamole, and guacamole with tomatoes. Weighted estimates described consumption prevalence, amount, form, self-selected eating occasion, location, and source. Nutrient contributions from avocado were calculated overall and by sex, age, and race/ethnicity. Results: 5.8% of participants consumed avocado. Prevalence was highest among women (6.9%), adults aged 19–50 years (7.4%), and Hispanic individuals (9.1%). Among consumers, the mean intake was 67.0 g/day. Plain avocado was the most common form (54.8%), and most intake occurred at dinner (43.4%) and at home (67.7%). Avocado was an important contributor to the mean daily intake among consumers for beta-cryptoxanthin (33.4%), alpha-carotene (27.0%), dietary fiber (19.9%), monounsaturated fatty acids (19.7%), and other nutrients. Conclusions: Although avocado consumption remains relatively modest, it contributes meaningfully to nutrient intake among avocado consumers. These findings provide descriptive insight into avocado consumption patterns and nutrient contributions in the U.S. population. Full article

Background/Objectives: Shift work and chronotype influence timing and type of food consumed, yet their combined influence is unclear. This study determined differences between temporal patterns of eating (times of first (FEO), last (LEO), and largest eating occasions (LarEO), duration of eating window (DEW), eating frequency) and nutrient intake of night shift workers on and off shift and the additional influence of chronotype. Methods: Participants (46.6 ± 10.2 years, BMI: 33.9 ± 5.6 kg/m², male/female: 57/72) completed work/sleep/food diaries, and the Composite Scale of Morningness. Dietary profiles were characterized by day type as follows: morning shift (MS), 1st night shift (1stNS), subsequent night shifts (SNS), 1st day off after night shifts (1stDONS), or other days off (DO). Results: Across day types, there were significant differences in FEO (p < 0.001), LEO (p < 0.001), LarEO (p = 0.025), DEW (p < 0.001), eating frequency (p = 0.003), total energy (p = 0.022), and fibre intake (p < 0.001). Compared to MS, all night shifts had later FEO, LEO, and LarEO; 1stNS had longer DEW and higher fibre but no differences in frequency, energy, and macronutrient intake. Greater morningness was associated with earlier FEO, LEO, LarEO, and lower %energy from fat and saturated fat. Effect of chronotype on temporal eating patterns was not different across day types; there was a significant, positive relationship between morningness and %energy from carbohydrate (%Energy_CHO) on MS (p = 0.004) and 1stDONS (p = 0.040). Conclusions: Dietary habits of night shift workers vary by shift schedule and degree of morningness. Further studies will confirm if shift schedule is more influential than chronotype on shift workers’ dietary habits. Full article

Dairy foods are rich in nutrients and typically have a lower environmental impact than other animal-based products. Despite these benefits, in France dairy consumption is lower than recommended. This study sought to understand where in the diet dairy foods are consumed, with a view to identifying opportunities for increasing consumption. A characterisation study was conducted using the INCA3 database (n = 783, 324 males, aged 18–44 years). All eating episodes containing dairy products were classified by product type and five dimensions to characterise consumption: (1) amount consumed; (2) eaten or drunk; (3) sweet or savoury; (4) in combination with other foods or by itself; (5) time of day. A sixth dimension, meal or snack, was also based on time of day. The results showed that (1) an average of 246 g, 1126 kJ of dairy is consumed per person, per day; (2) more dairy sub-groups are eaten than drunk; (3) dairy is consumed in sweet and savoury dishes; (4) in combination with other foods, rarely by itself; (5, 6) and at traditional mealtimes, rarely as a snack. Suggestions can be made for increasing dairy consumption based on product type, eating occasion, and context, e.g., increasing availability in out-of-home settings, and considering new or unusual food combinations for new recipes. Full article

Background/Objectives: Nocturnal glucose regulation is a critical but underexplored determinant of next-day fasting glucose (FG), particularly in individuals with dysglycemia. This study examined the role of glucose levels after the last eating occasion (LEO) and during the overnight fast in predicting FG, considering the potential influence of carbohydrate content in LEO and insulin sensitivity. Methods: In a controlled 24 h protocol, 33 adults (50–75 years) with prediabetes or diet-controlled type 2 diabetes followed a standardized feeding schedule with meals at fixed times, including a LEO at 10:00 p.m. Continuous glucose monitoring was used to assess glucose during the 3 h postprandial period (LEO-PPGR) and two fasting intervals: chronological overnight fast (COF) and biological overnight fast (BOF). Associations with FG were tested using general linear models, adjusting for carbohydrate intake and insulin sensitivity (Matsuda index). Results: Glucose responses during LEO-PPGR—assessed by mean glucose, peak, and AUC—were strongly correlated with FG the next morning (r = 0.704, 0.535, and 0.708, p < 0.001). Similarly, glucose levels during COF and BOF were also correlated with FG (r = 0.878, p < 0.001 for both), but these associations weakened after adjustment for LEO carbohydrate content. The Matsuda index was positively correlated with glucose in all three periods (p < 0.05), yet its inclusion in the model attenuated all previously significant associations with FG. Conclusions: These findings suggest that the glycemic response to the last meal and subsequent overnight glucose levels contribute to next-day FG, but their impact is modulated by carbohydrate content and individual insulin sensitivity. Understanding nocturnal glycemic dynamics may inform strategies for improving metabolic outcomes in dysglycemia. Full article

Background/Objectives: Inadequate intake of indispensable amino acids (IAAs) is a significant challenge in vegan diets. Since IAAs are not produced or stored over long durations in the human body, regular and balanced dietary protein consumption throughout the day is essential for metabolic function. The objective of this study is to investigate the variation in protein and IAA intake across 24 h among New Zealand vegans with time-series clustering, using Dynamic Time Warping (DTW). Methods: This data-driven approach objectively categorised vegan dietary data into distinct clusters for protein intake and protein quality analysis. Results: Total protein consumed per eating occasion (EO) was 11.1 g, with 93.5% of the cohort falling below the minimal threshold of 20 g of protein per EO. The mean protein intake for each EO in cluster 1 was 6.5 g, cluster 2 was 11.4 g and only cluster 3 was near the threshold at 19.0 g. IAA intake was highest in cluster 3, with lysine and leucine being 3× higher in cluster 3 than cluster 1. All EOs in cluster 1 were below the reference protein intake relative to body weight, closely followed by cluster 2 (91.5%), while cluster 3 comparatively had the lowest EOs under this reference (31.9%). Conclusions: DTW produced three distinct dietary patterns in the vegan cohort. Further exploration of plant protein combinations could inform recommendations to optimise protein quality in vegan diets. Full article

Health disparities have been associated with diet quality inequalities. Study objectives were to determine if race and/or income were associated with the diet quality of White and African American urban women and to compare core food and beverage categories consumed at eating occasions by diet quality within race and income groups. Two 24 h dietary recalls were collected on 1219 women interviewed in the Healthy Aging in Neighborhoods of Diversity across the Life Span study, 2013–2017. Healthy Eating Index (HEI)-2010 scores were calculated. Linear regression Model 1 included race, marital status, and age. Model 2 included Model 1 variables plus income, education, literacy, employment, enough money for food, and food security. Core food categories and most frequently consumed items were identified at five eating occasions within the first and third tertile HEI-2010. Diet quality was associated with age, education, literacy, and employment. More fruit and vegetable categories at meals and snacks, and more water as a top beverage, were observed for women whose diets were in the third HEI-2010 tertile. The majority of foods reported by women in the first HEI-2010 tertile would be considered ultra-processed. The health benefits of consuming more minimally processed foods and unsweetened beverages may reduce health disparity gaps. Full article

Background: Wearable devices equipped with a range of sensors have emerged as promising tools for monitoring and improving individuals’ health and lifestyle. Objectives: Contribute to the investigation and development of effective and reliable methods for dietary monitoring based on raw kinetic data generated by wearable devices. Methods: This study uses resources from the NOTION study. A total of 20 healthy subjects (9 women and 11 men, aged 20–31 years) were equipped with two commercial smartwatches during four eating occasions under semi-naturalistic conditions. All meals were video-recorded, and acceleration data were extracted and analyzed. Food recognition on these features was performed using random forest (RF) models with 5-fold cross-validation. The performance of the classifiers was expressed in out-of-bag sensitivity and specificity. Results: Acceleration along the x-axis and power show the highest and lowest rates of median variable importance, respectively. Increasing the window size from 1 to 5 s leads to a gain in performance for almost all food items. The RF classifier reaches the highest performance in identifying meatballs (89.4% sensitivity and 81.6% specificity) and the lowest in identifying sandwiches (74.6% sensitivity and 72.5% specificity). Conclusions: Monitoring food items using simple wristband-mounted wearable devices is feasible and accurate for some foods while unsatisfactory for others. Machine learning tools are necessary to deal with the complexity of signals gathered by the devices, and research is ongoing to improve accuracy further and work on large-scale and real-time implementation and testing. Full article

Background/Objectives: This study aimed to examine associations between meal timing habits and sleep health in midlife Mexican women. Methods: Data comprised 379 midlife Mexican women who participated in a phone survey conducted within the Early Life Exposures in Mexico to Environmental Toxicants (ELEMENT) project during the early stages of the COVID-19 pandemic. Women answered questions related to meal habits and sleep duration, latency, and quality. We used linear regression to investigate the associations between meal timing, frequency of meals/snacks, eating window (duration between first and last eating occasion of the day), duration between last meal, bedtime, sleep duration, and logistic regression to examine the associations between meal timing, sleep latency, and sleep quality, adjusting for confounders. Results: Later timing of meals throughout the day, and a shorter interval between the last meal of the day and bedtime, were associated with prolonged sleep latency and worse sleep quality. Associations with sleep duration were mixed: a longer eating window and a later largest and last meal were each associated with shorter sleep duration, while a later first meal and a shorter interval between the last meal of the day and bedtime were associated with longer sleep duration. Conclusions: Meal timing habits are associated with sleep duration, latency, and quality in midlife women. Full article

Objective: This pilot cross-sectional study explored differences in dietary intake and eating behaviors between healthy adults and a group of adults taking insulin to manage diabetes. Methods: A characteristic questionnaire and up to four Automated Self-Administered 24-Hour dietary recalls were collected from 152 adults aged 18–65 years (96 healthy and 56 adults taking insulin) from Indiana and across the U.S. from 2022 to 2023. The macronutrient intake, diet quality via the Healthy Eating Index (HEI)-2015, eating frequency, and consistency of timing of eating were calculated and compared between the two groups using adjusted linear or logistic regression models. Results: The total mean HEI scores were very low, at 56 out of 100 and 49 out of 100 for the healthy and insulin-taking groups, respectively. Insulin-taking adults had significantly lower HEI total (p = 0.003) and component scores compared to the healthy group for greens and beans (2.0 vs. 3.0, p = 0.02), whole fruit (2.1 vs. 2.9, p = 0.05), seafood and plant proteins (2.1 vs. 3.3, p = 0.004), and saturated fats (3.7 vs. 5.4, p = 0.05). Eating frequency was significantly lower in the insulin-taking group than in the healthy group (3.0 vs. 3.4 eating occasions/day, p = 0.05). Conclusion: Evidence of the low diet quality and eating frequency of insulin takers may help inform and justify nutrition education to control and manage diabetes. Full article

Background: Previous studies have shown that meal timing, poor sleep quality, and chronotype may play a relevant role in the development of type 2 diabetes mellitus (T2DM). However, its relationship with macronutrients by eating occasions has not been explored deeply. Objective: Our aim was to estimate the association between chrono-nutrition, sleep quality, chronotype, and the prevalence of T2DM. Methods: This cross-sectional study included a subset of 3465 middle-aged Caucasian adults (2068 women) from the European Prospective Investigation into Cancer and Nutrition (EPIC) Spain cohort study. In the 2017–18 follow-up, we assessed chronotype, sleep quality, diet, and sociodemographic data using validated questionnaires. Further, we used blood samples to determine serum levels of glucose. We defined a case of T2DM when serum glucose concentration was ≥126 mg/dL or when participants self-reported diabetes. Results: A higher prevalence of T2DM was associated with poor sleep quality (OR_poorvsgood = 2.90, 95% CI = 1.30, 6.28). Carbohydrate intake at breakfast was inversely associated with the prevalence of T2DM (OR = 0.75, 95% CI = 0.66, 0.85). Finally, lipid intake at breakfast was associated with a 13% higher prevalence of T2DM (OR = 1.13, 95% CI = 1.01, 1.26) for each 1 standard deviation (1-SD) increase. Conclusions: This study concludes that a higher content of carbohydrates at breakfast is correlated with a reduced prevalence of T2DM, while higher lipids intake at breakfast is associated with a higher prevalence of T2DM. Furthermore, poor sleep quality is a potential factor associated with an elevated prevalence of T2DM. Our results emphasize the need for prospective studies to validate and strengthen these observed associations. Full article

Chrononutrition is a rapidly evolving field of nutritional epidemiology that addresses the complex relationship between temporal eating patterns, circadian rhythms, and metabolic health, but most prior research has focused on the cardiometabolic consequences of time-restricted feeding and intermittent fasting. The purpose of this topical review is to summarize epidemiological evidence from observational and intervention studies regarding the role of chrononutrition metrics related to eating timing and regularity in cardiometabolic health preservation and cardiovascular disease prevention. Observational studies are limited due to the lack of time-stamped diet data in most population-based studies. Findings from cohort studies generally indicate that breakfast skipping or the later timing of the first eating occasion, a later lunch and dinner, and a greater proportion of caloric intake consumed in the evening are associated with adverse cardiometabolic outcomes, including higher risk for coronary heart disease, hypertension, type 2 diabetes, obesity, dyslipidemia, and systemic inflammation. Randomized controlled trials are also limited, as most in the field of chrononutrition focus on the cardiometabolic consequences of time-restricted feeding. Overall, interventions that shift eating timing patterns to earlier in the day and that restrict evening caloric intake tend to have protective effects on cardiometabolic health, but small sample sizes and short follow-up are notable limitations. Innovation in dietary assessment approaches, to develop low-cost validated tools with acceptable participant burden that reliably capture chrononutrition metrics, is needed for advancing observational evidence. Culturally responsive pragmatic intervention studies with sufficiently large and representative samples are needed to understand the impact of fixed and earlier eating timing schedules on cardiometabolic health. Additional research is warranted to understand the modifiable determinants of temporal eating patterns, to investigate the role of chrononutrition in the context of other dimensions of diet (quantity, quality, and food and nutrition security) in achieving cardiometabolic health equity, and to elucidate underlying physiological mechanisms. Full article

A healthy body mass contributes to a positive quality of life, and for overweight/obese individuals, weight loss of even modest proportions improves health-related outcomes. A novel approach to promoting body mass regulation is to pair exercise with high altitude, thereby upregulating metabolic processes and increasing caloric expenditure. As an added measure of body mass regulation, data suggest that high altitude stimulates the production of the appetite-suppressing hormone leptin. Issues arise, however, given that high altitude compromises aerobic exercise capacity. Whereas exercising at high altitude may compromise exercise intensity and duration, recovering at high altitude retains the integrity of exercise while still potentially conferring the benefits of the low oxygen environment on energy expenditure and energy intake. The purpose of this study was to perform a proof-of-concept pilot test on whether post-exercise exposure to a simulated high altitude influenced acute energy balance. Twelve healthy men and women ran for 30 min at a moderate intensity on two separate occasions. Following exercise, participants recovered for 30 min while breathing either sea level air or low oxygen air simulating high altitude (equivalent to 4500 m elevation). Blood samples and hunger ratings were collected pre-exercise and post-recovery. Heart rate was recorded throughout exercise and recovery and used to calculate caloric expenditure. Post-exercise energy expenditure was significantly higher (p = 0.03) following high altitude recovery (139 ± 15 kcal) compared to sea-level recovery (98 ± 11 kcal). Participants reported a lower desire to eat when they recovered in the high altitude environment (p = 0.01), though post-recovery leptin concentrations were similar between the two conditions. Post-exercise exposure to a simulated high altitude environment represents a promising method for increasing daily caloric expenditure and lowering appetite. Given the pilot nature of this study, future research is needed to address the question of high altitude recovery on a larger sample over a longer time period and with robust measures of caloric expenditure. Full article

This study aimed to examine the relationship between the frequency of household shared meals and the intake of 17 food groups and 21 nutrients. Participants were 3310 men and 3386 women ≥20 years old living in a household of ≥2 members from 2018 and 2019 National Health and Nutrition Surveys in Japan. A one-day household dietary record was used to classify an individual’s shared meal frequency and dietary intake. A shared meal is defined as an eating occasion (i.e., breakfast, lunch, and dinner) where ≥1 food item—other than sugars, fats and oils, beverages, and condiments—was recorded with an assigned approximated shared proportion. The shared meal frequency for each individual was classified into one of four categories: 0, 1, 2, and 3 times/day. Dietary intake was compared across the shared meal categories adjusted for age, occupation, household size, meal skipping, snacking, residential areas, and within-household correlations. Both men and women who had more frequent shared meals showed higher intakes of potatoes, vegetables, mushrooms, and condiments but less confectioneries and beverages. A higher shared meal frequency was also related to a higher intake of many (12/21) nutrients (e.g., protein, dietary fiber, and potassium). However, in women, there was a positive association between shared meal frequency and sodium intake. A higher frequency of household shared meals may be related to a more favorable dietary intake; except for concerns about sodium intake in women. Full article

This observational pilot study examined the association between diet, meal pattern and glucose over a 2-week period under free-living conditions in 26 adults with dysglycemia (D-GLYC) and 14 with normoglycemia (N-GLYC). We hypothesized that a prolonged eating window and late eating occasions (EOs), along with a higher dietary carbohydrate intake, would result in higher glucose levels and glucose variability (GV). General linear models were run with meal timing with time-stamped photographs in real time, and diet composition by dietary recalls, and their variability (SD), as predictors and glucose variables (mean glucose, mean amplitude of glucose excursions [MAGE], largest amplitude of glucose excursions [LAGE] and GV) as dependent variables. After adjusting for calories and nutrients, a later eating midpoint predicted a lower GV (β = −2.3, SE = 1.0, p = 0.03) in D-GLYC, while a later last EO predicted a higher GV (β = 1.5, SE = 0.6, p = 0.04) in N-GLYC. A higher carbohydrate intake predicted a higher MAGE (β = 0.9, SE = 0.4, p = 0.02) and GV (β = 0.4, SE = 0.2, p = 0.04) in N-GLYC, but not D-GLYC. In summary, our data suggest that meal patterns interact with dietary composition and should be evaluated as potential modifiable determinants of glucose in adults with and without dysglycemia. Future research should evaluate causality with controlled diets. Full article