A generic coding approach for the examination of meal patterns

Dietary Intake Assessment Using a Novel, Generic Meal-Based Recall and a 24-Hour Recall: Comparison Study

BACKGROUND

Dietary intake assessment is an integral part of addressing suboptimal dietary intakes. Existing food-based methods are time-consuming and burdensome for users to report the individual foods consumed at each meal. However, ease of use is the most important feature for individuals choosing a nutrition or diet app. Intakes of whole meals can be reported in a manner that is less burdensome than reporting individual foods. No study has developed a method of dietary intake assessment where individuals report their dietary intakes as whole meals rather than individual foods.

OBJECTIVE

This study aims to develop a novel, meal-based method of dietary intake assessment and test its ability to estimate nutrient intakes compared with that of a web-based, 24-hour recall (24HR).

METHODS

Participants completed a web-based, generic meal-based recall. This involved, for each meal type (breakfast, light meal, main meal, snack, and beverage), choosing from a selection of meal images those that most represented their intakes during the previous day. Meal images were based on generic meals from a previous study that were representative of the actual meal intakes in Ireland. Participants also completed a web-based 24HR. Both methods were completed on the same day, 3 hours apart. In a crossover design, participants were randomized in terms of which method they completed first. Then, 2 weeks after the first dietary assessments, participants repeated the process in the reverse order. Estimates of mean daily nutrient intakes and the categorization of individuals according to nutrient-based guidelines (eg, low, adequate, and high) were compared between the 2 methods. P values of less than .05 were considered statistically significant.

RESULTS

In total, 161 participants completed the study. For the 23 nutrient variables compared, the median percentage difference between the 2 methods was 7.6% (IQR 2.6%-13.2%), with P values ranging from <.001 to .97, and out of 23 variables, effect sizes for the differences were small for 19 (83%) variables, moderate for 2 (9%) variables, and large for 2 (9%) variables. Correlation coefficients were statistically significant (P<.05) for 18 (78%) of the 23 variables. Statistically significant correlations ranged from 0.16 to 0.45, with median correlation of 0.32 (IQR 0.25-0.40). When participants were classified according to nutrient-based guidelines, the proportion of individuals who were classified into the same category ranged from 52.8% (85/161) to 84.5% (136/161).

CONCLUSIONS

A generic meal-based method of dietary intake assessment provides estimates of nutrient intake comparable with those provided by a web-based 24HR but with varying levels of agreement among nutrients. Further studies are required to refine and improve the generic recall across a range of nutrients. Future studies will consider user experience including the potential feasibility of incorporating image recognition of whole meals into the generic recall.

Identifying usual food choices with avocados in a clinical trial cohort of overweight and obese adults in Australia

BACKGROUND

Consumption of avocados has been suggested to be beneficial for weight control, however, limited research is available about the related food choices. Understanding the food choices associated with avocados at meal occasions may further aid behavioural strategies to lose weight. The present study used a systematic approach to develop an avocado-specific food database, with the aim to explore food choices related to avocados at meal occasions as reported by overweight and obese volunteers in weight loss clinical trials.

METHODS

The avocado-specific database was based on AUSNUT 2011-13 food composition database structure and was developed via a systematic approach, which determined the avocado content of Australian foods and beverages. Baseline usual food intake data was retrospectively pooled from four food-based clinical trials (n = 758). The Apriori algorithm of association rules, a two-step descriptive method was used to identify food choices associated with avocados at different meal occasions using a nested hierarchical food group classification system.

RESULTS

The avocado database identified 34 avocados and avocado-containing foods and beverages. The proportion of avocado consumers in the pooled cohort was 51.3% (n = 389), with an average avocado intake of 21.57 ± 36.75 grams per day. Avocados were found to be closely related to other food groups at all of the food group levels at main meal occasions. A total of 68 food items containing avocados were identified for avocado consumers at the breakfast, lunch and dinner meals.

CONCLUSION

The avocado specific database provides a snapshot of the foods and beverages which contain avocados. Enumerating the full range of food choices in relation to avocado consumption should provide examples of food choices that people might consider in their efforts to increase their avocado consumption.

A Clustering Approach to Meal-Based Analysis of Dietary Intakes Applied to Population and Individual Data

BACKGROUND

Examination of meal intakes can elucidate the role of individual meals or meal patterns in health not evident by examining nutrient and food intakes. To date, meal-based research has been limited to focus on population rather than individual intakes, without considering portions or nutrient content when characterizing meals.

OBJECTIVES

We aimed to characterize meals commonly consumed, incorporating portions and nutritional content, and to determine the accuracy of nutrient intake estimates using these meals at both population and individual levels.

METHODS

The 2008-2010 Irish National Adult Nutrition Survey (NANS) data were used. A total of 1500 participants, with a mean ± SD age of 44.5 ± 17.0 y and BMI of 27.1 ± 5.0 kg/m2, recorded their intake using a 4-d weighed food diary. Food groups were identified using k-means clustering. Partitioning around the medoids clustering was used to categorize similar meals into groups (generic meals) based on their Nutrient Rich Foods Index (NRF9.3) score and the food groups that they contained. The nutrient content for each generic meal was defined as the mean content of the grouped meals. Seven standard portion sizes were defined for each generic meal. Mean daily nutrient intakes were estimated using the original and the generic data.

RESULTS

The 27,336 meals consumed were aggregated to 63 generic meals. Effect sizes from the comparisons of mean daily nutrient intakes (from the original compared with generic meals) were negligible or small, with P values ranging from <0.001 to 0.941. When participants were classified according to nutrient-based guidelines (high, adequate, or low), the proportion of individuals who were classified into the same category ranged from 55.3% to 91.5%.

CONCLUSIONS

A generic meal-based method can estimate nutrient intakes based on meal rather than food intake at the sample population and individual levels. Future work will focus on incorporating this concept into a meal-based dietary intake assessment tool.

Meal-specific dietary patterns and their contribution to habitual dietary patterns in the Iranian population

Recent studies have focused on habitual intake without addressing meal-specific intakes. We aimed to identify meal-specific dietary patterns and their contribution to habitual dietary patterns. This cross-sectional study was conducted on 838 adults, both sexes who attended the health centres in Tehran. Dietary data were recorded by three 24-h dietary recalls (24hDR). Dietary patterns were identified by using principal component analysis on meal-specific and overall food intakes. Intraclass correlation (ICC) was used as a measurement of consistency across meals and days. Correlation analysis and linear regression (partial R2) were used for meals contribution. Four habitual dietary patterns were derived from average dietary intake of 3-d 24hDR labelled as 'Western', 'Healthy', 'Traditional' and 'Legume and broth'. Also, we identified two major dietary patterns on each meal level (factor 1 and 2 for breakfast, lunch, afternoon snack and dinner). The highest contribution of energy intake was observed in lunch (25·7 %), followed by dinner (20·81 %). Consistency of food groups was the highest across days (ICC tea = 0·58) and breakfasts (ICC tea = 0·60). Dinner had a strong correlation coefficient with the 'Western' habitual dietary pattern then followed by lunch. Similarly, dinner and lunch contributed the most (r and partial R2) to the 'Western' habitual dietary pattern. Our results suggest that habitual dietary patterns to several extents are formed at meal levels, and dinner has a greater contribution to the habitual dietary patterns in Iranian people. This may help planning for local dietary guidelines according to the time of eating to promote public health.

Meal Pattern Analysis in Nutritional Science: Recent Methods and Findings

There is a scarcity of dietary intake research focusing on the intake of whole meals rather than on the nutrients and foods of which those meals are composed. This growing area of research has recently begun to utilize advanced statistical techniques to manage the large number of variables and permutations associated with these complex meal patterns. The aim of this narrative review was to evaluate those techniques and the meal patterns they detect. The 10 observational studies identified used techniques such as principal components analysis, clustering, latent class analysis, and decision trees. They examined meal patterns under 3 categories: temporal patterns (relating to the timing and distribution of meals), content patterns (relating to combinations of foods within a meal and combinations of those meals over a day), and context patterns (relating to external elements of the meal, such as location, activities while eating, and the presence or absence of others). The most common temporal meal patterns were the 3 meals/d pattern, the skipped breakfast pattern, and a grazing pattern consisting of smaller but more frequent meals. The 3 meals/d pattern was associated with increased diet quality compared with the other 2 patterns. Studies identified between 7 and 12 content patterns with limited similarities between studies and no clear associations between the patterns and diet quality or health. One study simultaneously examined temporal and context meal patterns, finding limited associations with diet quality. No study simultaneously examined other combinations of meal patterns. Future research that further develops the statistical techniques required for meal pattern analysis is necessary to clarify the relations between meal patterns and diet quality and health.

Using food network analysis to understand meal patterns in pregnant women with high and low diet quality

BACKGROUND

Little is known about how meal-specific food intake contributes to overall diet quality during pregnancy, which is related to numerous maternal and child health outcomes. Food networks are probabilistic graphs using partial correlations to identify relationships among food groups in dietary intake data, and can be analyzed at the meal level. This study investigated food networks across meals in pregnant women and explored differences by overall diet quality classification.

METHODS

Women were asked to complete three 24-h dietary recalls throughout pregnancy (n = 365) within a prospective cohort study in the US. Pregnancy diet quality was evaluated using the Healthy Eating Index-2015 (HEI, range 0-100), calculated across pregnancy. Networks from 40 food groups were derived for women in the highest and lowest HEI tertiles at each participant-labeled meal (i.e., breakfast, lunch, dinner, snacks) using Gaussian graphical models. Network composition was qualitatively compared across meals and between HEI tertiles.

RESULTS

In both HEI tertiles, breakfast food combinations comprised ready-to-eat cereals with milk, quick breads with sweets (e.g., pancakes with syrup), and bread with cheese and meat. Vegetables were consumed at breakfast among women in the high HEI tertile only. Combinations at lunch and dinner were more varied, including vegetables with oils (e.g., salads) in the high tertile and sugary foods with nuts, fruits, and milk in the low tertile at lunch; and cooked grains with fats (e.g., pasta with oil) in the high tertile and potatoes with vegetables and meat in the low tertile at dinner. Fried potatoes, sugar-sweetened beverages, and sandwiches were consumed together at all main meals in the low tertile only. Foods were consumed individually at snacks in both tertiles; the most commonly consumed food were fruits in the high HEI tertile and cakes & cookies in the low tertile.

CONCLUSIONS

In this cohort of pregnant women, food network analysis indicated that food combinations differed by meal and between HEI tertiles. Meal-specific patterns that differed between diet quality tertiles suggest potential targets to improve food choices at meals; the impact of meal-based dietary modifications on intake of correlated foods and on overall diet quality should be investigated in simulations and intervention studies.

TRIAL REGISTRATION

PEAS was registered with number NCT02217462 in Clinicaltrials.gov on August 13, 2014.

What do Australian adults eat for breakfast? A latent variable mixture modelling approach for understanding combinations of foods at eating occasions

BACKGROUND

The patterning of food intake at eating occasions is a poorly understood, albeit important, step towards achieving a healthy dietary pattern. However, to capture the many permutations of food combinations at eating occasions, novel analytic approaches are required. We applied a latent variable mixture modelling (LVMM) approach to understand how foods are consumed in relation to each other at breakfast.

METHODS

Dietary intake at breakfast (n = 8145 occasions) was assessed via 24-h recall during the 2011-12 Australian National Nutrition and Physical Activity Survey (n = 3545 men and n = 4127 women, ⩾19 y). LVMM was used to determine breakfast food profiles based on 35 food group variables, reflecting compliance with Australian Dietary Guidelines. F and adjusted-chi2 tests assessed differences in timing of consumption and participant characteristics between the breakfast profiles. Regression models, adjusted for covariates, were used to examine associations between breakfast food profiles and objective adiposity measures (BMI and waist circumference).

RESULTS

Five distinct profiles were found. Three were similar for men and women. These were labelled: "Wholegrain cereals and milks" (men: 16%, women: 17%), "Protein-foods" (men and women: 11%) and "Mixed cereals and milks" (men: 33%, women: 37%). Two "Breads and spreads" profiles were also found that were differentiated by their accompanying beverages (men) or type of grain (women). Profiles were found to vary by timing of consumption, participant characteristics and adiposity indicators. For example, the "Protein-foods" profile occurred more frequently on weekends and after 9 am. Men with a "Bread and spreads (plus tea/coffee)" profile were older (P < 0.001) and had lower income and education levels (P < 0.05), when compared to the other profiles. Women with a "Protein-foods" profile were younger (P < 0.001) and less likely to be married (P < 0.01). Both men and women with a "Wholegrain cereals and milks" profile had the most favourable adiposity estimates (P < 0.05).

CONCLUSIONS

We identified five breakfast food profiles in adults that varied by timing of consumption, participant characteristics and adiposity indicators. LVMM was a useful approach for capturing the complexity of food combinations at breakfast. Future research could collect contextual information about eating occasions to understand the complex factors that influence food choices.

Identification of Dish-Based Dietary Patterns for Breakfast, Lunch, and Dinner and Their Diet Quality in Japanese Adults

We identified dish-based dietary patterns for breakfast, lunch, and dinner and assessed the diet quality of each pattern. Dietary data were obtained from 392 Japanese adults aged 20–69 years in 2013, using a 4 d dietary record. K-means cluster analysis was conducted based on the amount of each dish group, separately for breakfasts (n = 1462), lunches (n = 1504), and dinners (n = 1500). The diet quality of each dietary pattern was assessed using the Healthy Eating Index 2015 (HEI-2015) and Nutrient-Rich Food Index 9.3 (NRF9.3). The extracted dietary patterns were as follows: ‘bread-based’ and ‘rice-based’ for breakfast; ‘bread’, ‘rice-based’, ‘ramen’, ‘udon/soba’, and ‘sushi/rice bowl dishes’ for lunch; and ‘miscellaneous’, ‘meat dish and beer’, and ‘hot pot dishes’ for dinner. For breakfast, the HEI-2015 and NRF9.3 total scores were higher in the ‘rice-based’ pattern than the ‘bread-based’ pattern. For lunch, the HEI-2015 and NRF9.3 total scores were relatively high in the ‘rice-based’ pattern and low in the ‘ramen’ pattern. For dinner, the HEI-2015 total score was the highest in the ‘meat dish and beer’ pattern, and the NRF9.3 total score was higher in the ‘hot pot dishes’ than the ‘miscellaneous’ pattern. These results suggested that breakfast, lunch, and dinner have distinctive dietary patterns with different diet qualities.

Identifying Usual Food Choice Combinations With Walnuts: Analysis of a 2005-2015 Clinical Trial Cohort of Overweight and Obese Adults

Consumption of nuts has been associated with a range of favorable health outcomes. Evidence is now emerging to suggest that walnuts may also play an important role in supporting the consumption of a healthy dietary pattern. However, limited studies have explored how walnuts are eaten at different meal occasions. The aim of this study was to explore the food choices in relation to walnuts at meal occasions as reported by a sample of overweight and obese adult participants of weight loss clinical trials. Baseline usual food intake data were retrospectively pooled from four food-based clinical trials (n = 758). A nut-specific food composition database was applied to determine walnut consumption within the food intake data. The a priori algorithm of association rules was used to identify food choices associated with walnuts at different meal occasions using a nested hierarchical food group classification system. The proportion of participants who were consuming walnuts was 14.5% (n = 110). The median walnut intake was 5.14 (interquartile range, 1.10–11.45) g/d. A total of 128 food items containing walnuts were identified for walnut consumers. The proportion of participants who reported consuming unsalted raw walnut was 80.5% (n = 103). There were no identified patterns to food choices in relation to walnut at the breakfast, lunch, or dinner meal occasions. A total of 24 clusters of food choices related to walnuts were identified at others (meals). By applying a novel food composition database, the present study was able to map the precise combinations of foods associated with walnuts intakes at mealtimes using data mining. This study offers insights into the role of walnuts for the food choices of overweight adults and may support guidance and dietary behavior change strategies.

Frequency of Normal Birth Length and Its Determinants: A Cross-Sectional Study in Newborns

Objectives

There are several factors that may affect the length and height of the infant. Maternal factors include a wide array of factors (anthropometric, hematological, or genetic), which can affect newborn health determinants. The objective of this study was to evaluate the frequency of normal birth length and its determinants in newborns.

Methods

This retrospective cross-sectional study was carried out at the Obstetrics and Gynaecological Department of Hamdard Hospital, Karachi, Pakistan, from March 1, 2019, to August 31, 2019. The relevant data were gathered by trained data collectors with the help of a structured questionnaire designed specifically for the study after taking written informed consent from all the participants. Data analysis was performed using Statistical Package for Social Sciences Version 20. Binary logistic regression was applied to develop a risk assessment model for the study outcome.

Results

Out of 195 pregnant mothers, 57 (29.2%) had low birth weight infants. Mean age of mothers was 29.29±5.22 years, 142 (72.8%) had BMI of 25.0 or more, 102 (52.3%) had hemoglobin between 10 to 11 mg/dL, 172 (88.2%) used to take vitamin C and iron during pregnancy, 136 (69.7%) consumed extra meals during pregnancy, and only 5 (2.6%) were tobacco smokers/chewers. Hundred (51.3%) newborns had normal birth length, i.e., >48 cm. The mother's mid-arm circumference > 22 cm (adjusted odds ratio [AOR]: 4.719; 95% CI: 2.337-9.527; p<0.001), consumption of extra meals during pregnancy (AOR: 3.947; 95% CI: 1.627-9.574; p=0.002), hemoglobin > 11 mg/dL (AOR: 4.314; 95% CI: 1.779-10.463; p=0.001), and adequate rest during pregnancy (AOR: 3.798; 95% CI: 1.464-9.848; p=0.006) were significantly associated with normal birth length of the infants, i.e., >48 cm.

Conclusions

Mother's mid-arm circumference > 22 cm, consumption of extra meals during pregnancy, hemoglobin > 11 mg/dL, and adequate rest during pregnancy were found to be significant predictors of normal birth length of the infants.

Future Directions for Integrative Objective Assessment of Eating Using Wearable Sensing Technology

Established methods for nutritional assessment suffer from a number of important limitations. Diaries are burdensome to complete, food frequency questionnaires only capture average food intake, and both suffer from difficulties in self estimation of portion size and biases resulting from misreporting. Online and app versions of these methods have been developed, but issues with misreporting and portion size estimation remain. New methods utilizing passive data capture are required that address reporting bias, extend timescales for data collection, and transform what is possible for measuring habitual intakes. Digital and sensing technologies are enabling the development of innovative and transformative new methods in this area that will provide a better understanding of eating behavior and associations with health. In this article we describe how wrist-worn wearables, on-body cameras, and body-mounted biosensors can be used to capture data about when, what, and how much people eat and drink. We illustrate how these new techniques can be integrated to provide complete solutions for the passive, objective assessment of a wide range of traditional dietary factors, as well as novel measures of eating architecture, within person variation in intakes, and food/nutrient combinations within meals. We also discuss some of the challenges these new approaches will bring.

Food Combinations in Relation to the Quality of Overall Diet and Individual Meals in Japanese Adults: A Nationwide Study

We examined food combinations in relation to the quality of the overall diet and individual meals using a newly developed food combination questionnaire (FCQ) in a nationwide sample of Japanese adults aged 19–80 years (n = 2233). The quality of the overall diet and of each meal was assessed by the Healthy Eating Index-2015 (HEI-2015) and Nutrient-Rich Food Index 9.3 (NRF9.3). For all main meals (breakfast, lunch, and dinner), the most commonly consumed food combinations consisted of ‘rice, total vegetables, and tea and coffee’. Consistently positive associations between these food combinations and diet quality were found for breakfast (Spearman r: ≥0.46). Positive rather weak associations between these food combinations and diet quality were also observed for lunch (Spearman r: ≤0.48). Conversely, the associations were inconsistent for dinner: inverse associations with HEI-2015 (Spearman r: ≤−0.35) and generally weak positive associations with NRF9.3 (Spearman r: ≥0.09). For snacks, the most commonly consumed food combinations consisted of ‘confectioneries and tea and coffee’, but these showed rather weak associations with diet quality. Similar results were obtained when associations with the quality of overall diet were investigated. The FCQ may be useful in capturing the complex nature of food combinations in Japanese adults.

Associations between maternal dietary patterns and infant birth weight, small and large for gestational age in the Norwegian Mother and Child Cohort Study

BACKGROUND/OBJECTIVES

To assess whether quality of maternal diet affects birth weight and the risk of small for gestational age (SGA) and/or large for gestational age (LGA) babies.

SUBJECTS/METHODS

This study is based on the Norwegian Mother and Child Cohort Study (MoBa) and includes 65,904 pregnant women who answered a validated food frequency questionnaire at mid-pregnancy. Three maternal dietary patterns were extracted based on characteristics of food items in each pattern. From these we created four non-overlapping groups: "high prudent," "high Western," "high traditional," and "mixed". We obtained information about birth weight from the Norwegian Medical Birth Registry and calculated birth weight z-scores, SGA, and LGA according to an ultrasound-based, population-based, and a customized growth standards. Associations were studied by linear and multiple logistic regression.

RESULTS

Compared to the high Western group, the high prudent group was associated with lower birth weight (βultrasound z-scores -0.041 (95% confidence interval (CI): -0.068, -0.013)) and the high traditional group with higher birth weight (βultrasound 0.067 (95% CI: 0.040, 0.094)) for all three growth standards. The high prudent pattern was associated with increased SGA risk (SGAultrasound odds ratio (OR) 1.25 (95% CI: 1.02, 1.54)) and decreased LGA risk (LGApopulation OR 0.84 (95% CI: 0.75, 0.94)), while the high traditional group on the contrary was associated with decreased SGA (SGAcustomized OR 0.92 (95% CI: 0.84, 0.99)) and increased LGA risk (LGApopulation OR 1.12 (95% CI: 1.02, 1.24)).

CONCLUSIONS

Food quality was associated with birth weight in this well-nourished Norwegian population. Food quality may affect a woman's risk of giving birth to a SGA or LGA baby.

Associations of food groups and cardiometabolic and inflammatory biomarkers: does the meal matter?

Increased attention has been paid to circadian patterns and how predisposition to metabolic disorders can be affected by meal timing. Currently, it is not clear which role can be attributed to the foods selected at meals. On a cross-sectional sub-cohort study (815 adults) within the European Prospective Investigation into Cancer and Nutrition-Potsdam study, we investigated whether the same foods (vegetables, fruits, refined grains, whole grains, red and processed meats) eaten at different meals (breakfast, lunch or dinner) show different associations with biomarkers of cardiometabolic risk. Meal-specific usual intakes were calculated from multiple 24-h dietary recalls. Multivariable-adjusted linear regression models showed that intake of vegetables at breakfast was associated with lower LDL-cholesterol (-0·37 mmol/l per 50 g; 95 % CI -0·61, -0·12) and vegetables at dinner was associated with higher HDL-cholesterol (0·05 mmol/l per 50 g; 95 % CI 0, 0·10). Fruit intake at breakfast was associated with lower glycated Hb (HbA1c) (-0·06 % per 50 g; 95 % CI -0·10, -0·01) and fruits at dinner with lower C-reactive protein (CRP) (-0·21 mg/l per 50 g; 95 % CI -0·42, -0·01). Red and processed meat intake at breakfast was associated with higher HbA1c (0·25 % per 50 g; 95 % CI 0·05, 0·46) and CRP (0·76 mg/l per 50 g; 95 % CI 0·15, 1·36). Our results suggest that by preferring fruits and vegetables and avoiding red and processed meats at specific meals (i.e. breakfast and dinner), cardiometabolic profiles and ultimately chronic disease risk could be improved. Lunch seemed to be a less important meal in terms of food-biomarker associations.

The Association of Breakfast Frequency and Cardiovascular Disease (CVD) Risk Factors among Adolescents in Malaysia

Breakfast frequency is associated with cardiovascular disease (CVD) risk in Western populations, possibly via the types of food eaten or the timing of food consumption, but associations in Malaysian adolescents are unknown. While the timing of breakfast is similar, the type of food consumed at breakfast in Malaysia differs from Western diets, which allows novel insight into the mechanisms underlying breakfast-CVD risk associations. We investigated foods eaten for breakfast and associations between breakfast frequency and CVD risk factors in the Malaysian Health and Adolescents Longitudinal Research Team study (MyHeARTs). Breakfast (frequency of any food/drink reported as breakfast in 7-day diet history interviews) and CVD risk factors (body mass index (BMI), waist circumference, fasting blood glucose, triacylglycerol, total cholesterol, high-density lipoprotein (HDL), low-density lipoprotein (LDL), and systolic and diastolic blood pressure) were cross-sectionally associated using linear regression adjusting for potential confounders (n = 795, age 13 years). Twelve percent of adolescents never ate breakfast and 50% ate breakfast daily, containing mean (SD) 400 (±127) kilocalories. Commonly consumed breakfast foods were cereal-based dishes (primarily rice), confectionery (primarily sugar), hot/powdered drinks (primarily Milo), and high-fat milk (primarily sweetened condensed milk). After adjustment, each extra day of breakfast consumption per week was associated with a lower BMI (-0.34 kg/m², 95% confidence interval (CI) -0.02, -0.66), and serum total (-0.07 mmol/L 95% CI -0.02, -0.13) and LDL (-0.07 mmol/L 95% CI -0.02, -0.12) cholesterol concentrations. Eating daily breakfast in Malaysia was associated with slightly lower BMI and total and LDL cholesterol concentrations among adolescents. Longitudinal studies and randomized trials could further establish causality.

Applying a meal coding system to 16-d weighed dietary record data in the Japanese context: towards the development of simple meal-based dietary assessment tools

Data on the combination of foods consumed simultaneously at specific eating occasions are scarce, primarily due to a lack of assessment tools. We applied a recently developed meal coding system to multiple-day dietary intake data for assessing its ability to estimate food and nutrient intakes and characterise meal-based dietary patterns in the Japanese context. A total of 242 Japanese adults completed sixteen non-consecutive-day weighed dietary records, including 14 734 eating occasions (3788 breakfasts, 3823 lunches, 3856 dinners and 3267 snacks). Common food group combinations were identified by meal type to identify a range of generic meals. Dietary intake was calculated on the basis of not only the standard food composition database but also the substituted generic meal database. In total, eighty generic meals (twenty-three breakfasts, twenty-one lunches, twenty-four dinners and twelve snacks) were identified. The Spearman correlation coefficients between food group intakes calculated based on the standard food composition database and the substituted generic meal database ranged from 0·26 to 0·85 (median 0·69). The corresponding correlations for nutrient intakes ranged from 0·17 to 0·82 (median 0·61). A total of eleven meal patterns were established using principal components analysis, and these accounted for 39·1 % of total meal variance. Considerable variation in patterns was seen in meal type inclusion and choice of staple foods (bread, rice and noodles) and drinks, and also in meal constituents. In conclusion, this study demonstrated the usefulness of a meal coding system for assessing habitual diet, providing a scientific basis towards the development of simple meal-based dietary assessment tools.

Regularity of Breakfast Consumption and Diet: Insights from National Adult Nutrition Survey

Breakfast is considered to be one of the most important meals of the day. Its omission has been reported to be associated with increased disease risk, such as obesity, diabetes, and coronary heart disease, as well as unhealthy lifestyle and lower dietary quality. Using data from the National Adult Nutrition Survey (NANS)-a food consumption survey conducted among 1500 Irish men and women over 18 years of age, residing in the Republic of Ireland at the time the survey was conducted-we aimed to characterize breakfast regularity, identify dietary patterns associated with regular breakfast consumption, and assess the nutritional quality of such dietary patterns, using the nutrient-rich food index score NRF9.3. We determined two breakfast regularity categories and assessed dietary quality, by means of adherence to the principal component analysis derived dietary patterns and the NRF9.3 dietary index. Regular breakfast consumers were identified as those who consumed breakfast 3⁻4 times out of the 4 days of the collection period; such consumers comprised the majority of the population (94.4%). They had the highest adherence to healthier dietary patterns, namely, the "vegetarian" (odds ratio (OR): 2.59: 95% Confidence Interval (CI): 1.40, 4.77), "fish and vegetables" (OR: 2.88: 95% CI: 1.63, 5.10), and "breakfast cereals" (OR: 4.62: 95% CI: 2.43, 8.79) dietary patterns. Breakfast significantly contributed to the daily micronutrient intake by providing, on average, 24% of dietary fiber, 32% of iron, 30% of calcium, 32% of folate, and 37% of riboflavin. The importance of regular breakfast consumption on those who skip breakfast should be highlighted, in order to improve compliance with nutritional recommendations and adherence to a healthy lifestyle.

Meal and habitual dietary networks identified through Semiparametric Gaussian Copula Graphical Models in a German adult population

Gaussian graphical models (GGMs) are exploratory methods that can be applied to construct networks of food intake. Such networks were constructed for meal-structured data, elucidating how foods are consumed in relation to each other at meal level. Meal-specific networks were compared with habitual dietary networks using data from an EPIC-Potsdam sub-cohort study. Three 24-hour dietary recalls were collected cross-sectionally from 815 adults in 2010-2012. Food intake was averaged to obtain the habitual intake. GGMs were applied to four main meals and habitual intakes of 39 food groups to generate meal-specific and habitual dietary networks, respectively. Communities and centrality were detected in the dietary networks to facilitate interpretation. The breakfast network revealed five communities of food groups with other vegetables, sauces, bread, margarine, and sugar & confectionery as central food groups. The lunch and afternoon snacks networks showed higher variability in food consumption and six communities were detected in each of these meal networks. Among the central food groups detected in both of these meal networks were potatoes, red meat, other vegetables, and bread. Two dinner networks were identified with five communities and other vegetables as a central food group. Partial correlations at meals were stronger than on the habitual level. The meal-specific dietary networks were only partly reflected in the habitual dietary network with a decreasing percentage: 64.3% for dinner, 50.0% for breakfast, 36.2% for lunch, and 33.3% for afternoon snack. The method of GGM yielded dietary networks that describe combinations of foods at the respective meals. Analysing food consumption on the habitual level did not exactly reflect meal level intake. Therefore, interpretation of habitual networks should be done carefully. Meal networks can help understand dietary habits, however, GGMs warrant validation in other populations.

Breakfast Consumption in the UK: Patterns, Nutrient Intake and Diet Quality. A Study from the International Breakfast Research Initiative Group

Breakfast consumption is associated with higher overall dietary adequacy; however, there is a lack of quantitative guidelines for optimal nutrient intakes at breakfast in the UK. This study aimed to investigate nutrient and food group intakes at breakfast and examine their relationship to overall Diet Quality (DQ). Data from the most recent National Diet and Nutrition Survey (NDNS, 2008⁻2014) were accessed to provide a representative sample (n = 8174) of the UK population, aged 5⁻96 years, mean age of 33 years. Food intake was measured by a 4-day estimated food diary and DQ was assessed by the Nutrient Rich Food Index 9.3 method. Energy- and socio-economic-adjusted nutrient and food group intakes were compared across age groups and DQ tertiles by ANCOVA. Breakfast contributed 20⁻22% to total energy intake. Breakfast intakes of carbohydrate and non-milk extrinsic sugars (NMES) were higher, and intakes of protein, total fat and saturated fatty acid (SFA) were lower, than relative daily intakes. Breakfast was particularly rich in B vitamins, vitamin D, calcium, iron, iodine and magnesium. From the lowest to the highest DQ tertile decreasing intakes of NMES, SFA and total fat and increasing intakes of carbohydrate, protein, fibre and most micronutrients were found. These findings could help to inform the development of nutrient-based recommendations for a balanced breakfast for the first time in the UK.

Identifying usual food choices at meals in overweight and obese study volunteers: implications for dietary advice

Understanding food choices made for meals in overweight and obese individuals may aid strategies for weight loss tailored to their eating habits. However, limited studies have explored food choices at meal occasions. The aim of this study was to identify the usual food choices for meals of overweight and obese volunteers for a weight-loss trial. A cross-sectional analysis was performed using screening diet history data from a 12-month weight-loss trial (the HealthTrack study). A descriptive data mining tool, the Apriori algorithm of association rules, was applied to identify food choices at meal occasions using a nested hierarchical food group classification system. Overall, 432 breakfasts, 428 lunches, 432 dinners and 433 others (meals) were identified from the intake data (n 433 participants). A total of 142 items of closely related food clusters were identified at three food group levels. At the first sub-food group level, bread emerged as central to food combinations at lunch, but unprocessed meat appeared for this at dinner. The dinner meal was characterised by more varieties of vegetables and of foods in general. The definitions of food groups played a pivotal role in identifying food choice patterns at main meals. Given the large number of foods available, having an understanding of eating patterns in which key foods drive overall meal content can help translate and develop novel dietary strategies for weight loss at the individual level.

Generic Meal Patterns Identified by Latent Class Analysis: Insights from NANS (National Adult Nutrition Survey)

Nutritional data reduction methods are widely applied in nutrition epidemiology in order to classify individuals into meaningful groups with similar dietary patterns. To date, none of the existing studies have applied latent class analysis to examine dietary patterns which include meal types consumed throughout a day. We investigated main meal patterns followed on weekend and weekdays, and evaluated their associations with cardio-metabolic biomarkers. The analyses were performed within the NANS (National Adult Nutrition Survey) a cross-sectional national food consumption survey of 1500 nationally representative Irish adults. A total number of seven dietary patterns were identified using latent class analysis. The typical meal pattern followed by the majority of the population was characterized by consumption of cereal or toast for breakfast, skipping or consuming a sandwich for light meal, and meat or fish with potatoes, pasta or vegetables for the main meal. Eating patterns differed on weekends, and those participants who consumed meat and eggs for breakfast instead of breakfast cereal and skipped light meal were more likely to have an unhealthier dietary pattern, a higher diastolic blood pressure, and increased serum ferritin. The application of data reduction techniques to simplify the multifaceted nature of dietary data is a useful approach to derive patterns, which might shed further light on the typical dietary patterns followed by populations.

Contribution to the understanding of how principal component analysis-derived dietary patterns emerge from habitual data on food consumption

Background

Principal component analysis (PCA) is a widely used exploratory method in epidemiology to derive dietary patterns from habitual diet. Such dietary patterns seem to originate from intakes on multiple days and eating occasions. Therefore, analyzing food intake of study populations with different levels of food consumption can provide additional insights as to how habitual dietary patterns are formed.

Objective

We analyzed the food intake data of German adults in terms of the relations among food groups from three 24-h dietary recalls (24hDRs) on the habitual, single-day, and main-meal levels, and investigated the contribution of each level to the formation of PCA-derived habitual dietary patterns.

Design

Three 24hDRs were collected in 2010-2012 from 816 adults for an European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam subcohort study. We identified PCA-derived habitual dietary patterns and compared cross-sectional food consumption data in terms of correlation (Spearman), consistency (intraclass correlation coefficient), and frequency of consumption across all days and main meals. Contribution to the formation of the dietary patterns was obtained through Spearman correlation of the dietary pattern scores.

Results

Among the meals, breakfast appeared to be the most consistent eating occasion within individuals. Dinner showed the strongest correlations with "Prudent" (Spearman correlation = 0.60), "Western" (Spearman correlation = 0.59), and "Traditional" (Spearman correlation = 0.60) dietary patterns identified on the habitual level, and lunch showed the strongest correlations with the "Cereals and legumes" (Spearman correlation = 0.60) habitual dietary pattern.

Conclusions

Higher meal consistency was related to lower contributions to the formation of PCA-derived habitual dietary patterns. Absolute amounts of food consumption did not strongly conform to the habitual dietary patterns by meals, suggesting that these patterns are formed by complex combinations of variable food consumption across meals. Dinner showed the highest contribution to the formation of habitual dietary patterns. This study provided information about how PCA-derived dietary patterns are formed and how they could be influenced.

Establishment of a Meal Coding System for the Characterization of Meal-Based Dietary Patterns in Japan

Background: Most studies on dietary patterns to date have focused on the daily intake of individual foods, rather than the combination of foods simultaneously consumed during specific eating occasions (breakfast, lunch, dinner, and snacks).Objective: We aimed to establish a meal coding system for characterizing meal-based dietary patterns in Japan.Methods: Dietary data used were from the 2012 National Health and Nutrition Survey, Japan, in which 1-d weighed dietary records were collected from 26,361 adults aged ≥20 y. The food diary was based on a typical Japanese eating pattern, which comprised breakfast, lunch, dinner, and snacks; these eating occasions were prescribed in the diary. A total of 94,439 eating occasions (25,187 breakfasts, 25,888 lunches, 26,248 dinners, and 17,116 snacks) were identified. For all meal types, common food group combinations were identified to produce a range of generic meals. These generic meals were then used in principal components analysis to establish meal patterns.Results: In total, 94 generic meals (24 breakfasts, 27 lunches, 26 dinners, and 17 snacks) were identified. The most frequently identified food group combination for all 3 main meals was "rice and vegetables" (9 generic meals for breakfast, 12 for lunch, and 16 for dinner), whereas "confectioneries and nonalcoholic and noncaloric beverages" was the most prevalent combination for snacks (3 generic meals). In total, 19 meal patterns were established by using principal components analysis, which accounted for 24.1% of total variance. Patterns ranged considerably with regard to meal-type inclusion and the selection of staple foods (rice, bread, and noodles) and beverages, as well as with regard to meal constituents.Conclusions: With the use of a meal coding system, we identified a wide range of meal-based dietary patterns in Japanese adults. This meal coding system may be useful in capturing and investigating the complex nature of Japanese meals and food combination patterns.

Ultra-processed foods in human health: a critical appraisal

The NOVA classification of foods proposes 4 categories: unprocessed or minimally processed foods, processed culinary ingredients, processed foods, and ultra-processed foods and drinks (UPFDs). It is argued that the latter relies heavily on modifications to foods, resulting in enhanced amounts of salt, added sugar, and fat as well as the use of additives in an attempt to make this food category highly palatable. It further argues that controlling food processing, rather than examining nutrients, should be foremost in shaping nutrition policy. This commentary challenges many of the basic arguments of using the NOVA food classification system to examine the link between food and health. We believe that there is no evidence to uphold the view that UPFDs give rise to hyperpalatable foods associated with a quasi-addictive effect and that the prevailing European Union and US data fail to uphold the assertion that UPFDs, which dominate energy intake, give rise to dietary patterns that are low in micronutrients. With regard to the use of the NOVA food classification in the development of food-based dietary guidelines, we show that the very broad definition of UPFDs makes this impossible. Finally, the available evidence does not support the view that the globalization of food is the driver of increased intakes of UPFDs in low- to middle-income countries but rather that this is driven by small indigenous companies. On balance, therefore, there seems to be little advantage from the use of the NOVA classification compared with the current epidemiologic approach, which relies on the linkage of nutrient intakes to chronic disease with subsequent identification of foods that merit consideration in public health nutrition strategies.

Comparison of a Web-Based 24-h Dietary Recall Tool (Foodbook24) to an Interviewer-Led 24-h Dietary Recall

Web-based tools have the potential to reduce the cost of dietary assessment; however, it is necessary to establish their performance compared to traditional dietary assessment methods. This study aims to compare nutrient and food intakes derived from Foodbook24 to those obtained from an interview-led 24-h dietary recall (24HDR). Seventy-nine adult participants completed one self-administered 24HDR using Foodbook24 and one interviewer-led 24HDR on the same day. Following a 10 days wash-out period the same process was completed again in opposite order to the previous study visit. Statistical analysis including Spearman’s rank order correlation, Mann-Whitney U tests, cross-classification analysis, and “Match”, “Omission”, and “Intrusion” rates were used to investigate the relationship between both methods. Strong, positive correlations of nutrient intake estimated using both methods was observed (r_s = 0.6–1.0; p < 0.001). The percentage of participants classified into the same tertile of nutrient intake distribution using both methods ranged from 58% (energy) to 82% (vitamin D). The overall match rate for food intake between both methods was 85%, while rates for omissions and intrusions were 11.5% and 3.5%, respectively. These results, alongside the reduced cost and participant burden associated with Foodbook24, highlight the tool’s potential as a viable alternative to the interviewer-led 24HDR.

Meal frequency patterns and glycemic properties of maternal diet in relation to preterm delivery: Results from a large prospective cohort study

Background

Dietary habits are linked to high maternal glucose levels, associated with preterm delivery. The aim of this study was to examine the associations between meal frequency and glycemic properties of maternal diet in relation to preterm delivery.

Methods

This prospective cohort study included 66,000 women from the Norwegian Mother and Child Cohort Study (MoBa). Meal frequency and food intake data were obtained from a validated food frequency questionnaire during mid-pregnancy. Principal component factor analysis was used with a data-driven approach, and three meal frequency patterns were identified: “snack meal”, “main meal”, and “evening meal”. Pattern scores were ranked in quartiles. Glycemic index and glycemic load were estimated from table values. Intakes of carbohydrates, added sugar, and fiber were reported in grams per day and divided into quartiles. Gestational age was obtained from the Medical Birth Registry of Norway. Preterm delivery was defined as birth at <37 gestational weeks. A Cox regression model was used to assess associations with preterm delivery.

Results

After adjustments, the “main meal” pattern was associated with a reduced risk of preterm delivery, with hazard ratios (HRs) of 0.89 (95% confidence interval (CI): 0.80, 0.98) and 0.90 (95% CI: 0.81, 0.99) for the third and fourth quartiles, respectively, and p for trend of 0.028. This was mainly attributed to the group of women with BMI ≥25 kg/m², with HRs of 0.87 (95% CI: 0.79, 0.96) and 0.89 (95% CI: 0.80, 0.98) for the third and fourth quartiles, respectively, and p for trend of 0.010. There was no association between glycemic index, glycemic load, carbohydrates, added sugar, fiber, or the remaining meal frequency patterns and preterm delivery.

Conclusion

Regular consumption of main meals (breakfast, lunch, dinner) was associated with a lower risk of preterm delivery. Diet should be further studied as potential contributing factors for preterm delivery.

Associations between Restrained Eating and the Size and Frequency of Overall Intake, Meal, Snack and Drink Occasions in the UK Adult National Diet and Nutrition Survey

Obesity is a global public health priority. Restrained eating is related to obesity and total energy intake but associations with the eating patterns are unclear. We examined the associations of restrained eating with the size and frequency of intake occasions among 1213 British adult (19-64 y) participants in a cross-sectional analysis of the UK National Diet and Nutrition Survey 2000. The Dutch Eating Behaviour Questionnaire assessed restrained eating. Overall intake occasions were all energy consumed in a 60 min period. A food-based classification separated intake occasions into meals, snacks, or drinks from seven-day weighed food diaries. Average daily frequency and size (kcal) of overall intake, meal, snack and drink occasions were calculated and associations with restrained eating were modelled using multiple linear regression including under-reporting of energy intake, age, gender, BMI, emotional eating, external eating and physical activity as covariates. Restrained eating was very weakly positively correlated with overall intake (r = 0.08, p<0.05) and meal frequency (r = 0.10, p<0.05) but not snack or drink frequency (r = 0.02 and -0.02 respectively). Adjusted regressions showed a one-point change in restrained eating was associated with 0.07 (95% CI 0.03, 0.11) more meal occasions/day and 0.13 (95% CI 0.01, 0.25) extra overall intake occasions/day. Overall intake occasion size was weakly negatively correlated with restrained eating regardless of type (r = -0.16 to -0.20, all p<0.0001). Adjusted regressions showed each one-point increase in restrained eating was associated with lower-energy meals (-15 kcal 95% CI -5.9, -24.2) and drinks (-4 kcal 95%CI -0.1, -8), but not snacks or overall intake occasions. Among a national sample of UK adults, greater restrained eating was associated with smaller and slightly more frequent eating, suggesting that restrained eaters restrict their energy intake by reducing meal/drink size rather than skipping snacks.