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Meal skipping and variables related to energy balance in adults: A brief review, with emphasis on the breakfast meal
Abstract
A popular notion regarding habitual meal skipping is that it leads to weight gain; however, there is little support for this idea in the scientific literature. Here we review the evidence both for and against this notion in adults (≥ 18 y), with, out of practicality, a primary focus on the breakfast meal. To date, few randomized controlled trials and prospective studies have been conducted on breakfast skipping and energy balance. Three acute feeding studies have been published which show equivocal results and do not strongly support an effect of breakfast skipping on variables related to energy balance. Four longer-term studies lasting 2-3 weeks have been published and are consistent with the acute feeding trials in that breakfast skipping or eating treatments did not materially impact weight change. Four prospective studies in which participants were followed over 3.7-10 years do suggest a potential role for skipping breakfast in weight gain. However, observational studies do not imply causality; therefore, longer term experimental trials are needed before a definitive conclusion can be made concerning the role of breakfast skipping in weight change.
... Meal skipping is one behaviour studied as a factor influencing weight outcomes and dietary quality, with most of the research focusing on skipping breakfast. Research on adults indicates that although those who regularly skip breakfast tend to have higher body weights than those who do not (3)(4)(5)(6) , there is little evidence that skipping breakfast contributes to this difference (5,(7)(8)(9) . A few studies that have attempted to identify the effect of skipping breakfast among US adults using dietary intake data and within-person changes in meal patterns find that skipping breakfast increases energy content consumed at lunch but reduces total daily energy intake (10,11) . ...
... Meal skipping is one behaviour studied as a factor influencing weight outcomes and dietary quality, with most of the research focusing on skipping breakfast. Research on adults indicates that although those who regularly skip breakfast tend to have higher body weights than those who do not (3)(4)(5)(6) , there is little evidence that skipping breakfast contributes to this difference (5,(7)(8)(9) . A few studies that have attempted to identify the effect of skipping breakfast among US adults using dietary intake data and within-person changes in meal patterns find that skipping breakfast increases energy content consumed at lunch but reduces total daily energy intake (10,11) . ...
Objective
To examine whether skipping breakfast or lunch increased the next meal’s energy content and changed total daily energy content and the quality of food intake measured by the 2010 Healthy Eating Index (HEI-2010).
Design
Means were compared across intake days and meal patterns. Multivariate individual fixed-effects model was used to account for individual food intake and diet quality preferences.
Setting
National Health and Nutrition Examination Survey, 2007–2016.
Participants
Adults aged 18 years or older who reported 2 d (24-h periods) of dietary intake and were not pregnant or lactating ( n 23 488).
Results
Adults consumed 193 more kJ at lunch after skipping breakfast and 783 more kJ at dinner after skipping breakfast and lunch. Skipping at least one meal reduced total daily intake between 1053 (breakfast) and 1464 (dinner) kJ and reduced the daily HEI score. Skipping breakfast or skipping lunch reduced the HEI component scores for fruit, whole grains, dairy and empty energy; skipping lunch reduced the component scores for fruit, vegetables, whole grain, dairy, seafood and plant protein, and empty energy. Skipping dinner reduced component scores for vegetables, greens and beans, dairy, protein food, seafood and plant proteins, and empty energy. Skipping one or more meals increased component scores for total vegetables (breakfast), whole grains (dinner), Na (lunch or dinner) and refined grains (breakfast, lunch or dinner).
Conclusions
Skipping meals (particularly dinner) reduces daily energy intake, but the reduction in daily diet quality (particularly when skipping breakfast) may impact health negatively over time.
... Eating rhythm is an integral part of healthy eating. A regular eating pattern including breakfast, lunch, dinner, and 1 to 2 snacks has been found to be associated with good diet quality [1], whereas skipping breakfast has been consistently found to associate with poor overall diet quality and exposure to weight gain [2,3]. In addition, eating less than 3 times a day negatively influences appetite control, and unplanned snacking and consumption of the major part of the energy at the end of the day seem unfavorable for weight balance [4,5]. ...
... The measured attitudes and motives remained unchanged except for a small increase in weight control motive among the participants of Contentment group. To sum up, the study results indicate that self-monitoring of eating occasions with an EMA tool might assist in battling against the growing tendency of irregular eating [9][10][11][12][13] and harms related to it [2,3,[6][7][8]. The tool might be useful especially for people who follow a grazing eating pattern with no clear meal times but frequent peaks of eating occasions during the day. ...
Background: Temporal aspects of eating are an integral part of healthy eating, and regular eating has been associated with good diet quality and more successful weight control. Unfortunately, irregular eating is becoming more common. Self-monitoring of behavior has been found to be an efficient behavioral change technique, but the solution should be simple enough to ensure long-lasting adherence.
Objective: This study aimed to explore the influence of self-monitoring of daily eating pattern with mobile phone app on eating rhythm, eating behavior tendencies, and the underlying motives and attitudes related to eating.
Methods: A mobile phone app, Button, was developed for effortless self-monitoring of eating rhythm. The feasibility of the app was tested in a 30-day intervention. The participants (N=74) recorded their eating occasions during the intervention by
pressing a button in the app widget.
Results: The average interval between meals increased (96 [SD 24] min during the first 10 days vs 109.1[SD 36.4] during the last 10 days) and the number of daily eating occasions decreased (4.9 [SD 0.9] during the first 10 days vs 4.4 [SD 0.9] during the last 10 days). The tendencies for cognitive restraint, emotional eating, and uncontrolled eating increased. Eating-related attitudes and motives remained largely unchanged.
Conclusions: These results indicate that a simple self-monitoring tool is able to draw a user’s attention to eating and is a potential tool to aid people to change their eating rhythm.
... The pattern that combines breakfast skippers and late eaters ("Lunch&Evening" energy pattern) shows a connection between these 2 behaviors. Many studies have previously assumed these are independent exposures (McCrory, 2014;Pendergast et al., 2016); however, this pattern analysis shows they are inherently linked. Overcompensation for the energy missed at breakfast seems to occur in these children. ...
... This might be explained by the lower satiety associated with skipping breakfast (compared with children who have breakfast) that leads to overeating later in the day. Over time, this would result in an unhealthy weight gain (McCrory, 2014). Another explanation might be that children who eat later in the night are not hungry in the morning when they wake up and, therefore, they skip breakfast. ...
The time of eating has been considered to have an important role in weight regulation. However, it is unknown if there are specific daily patterns of energy and macronutrient distribution that could be more beneficial for metabolic outcomes, especially obesity. This study aimed to assess the effect of time-of-day energy and macronutrient intake at 4 y of age on the weight status at 7 y of age. The study sample included 1961 children from the population-based birth cohort Generation XXI, with data on 3-day food diaries at 4 y and body mass index (BMI) z-scores at 7 y. Dietary patterns based on the collected data were obtained for the distribution of energy and macronutrients across eating occasions. Having a relatively higher energy intake at lunch and supper (OR = 1.19, 95% CI = 1.05 to 1.34) or at mid-afternoon (OR = 1.18, 95% CI = 1.05 to 1.34) at 4 y was associated with higher odds of becoming overweight/obese at 7 y. A relatively higher intake of fat at lunch was positively associated with later children’s odds for being overweight or obese (OR = 1.17, 95% CI = 1.03 to 1.32). These associations were independent of the effect on children’s eating behaviors related to appetite. Our results also show a detrimental relation between skipping breakfast and eating late in the day and children’s body weight. Considering all daily eating occasions, a higher proportion of energy and macronutrient intake at the main meals and a lower proportion during the afternoon and evening seems to be more beneficial for children’s weight. These results emphasize the important role of daily food intake rhythm on excessive weight gain in childhood.
... Eating rhythm is an integral part of healthy eating. A regular eating pattern including breakfast, lunch, dinner, and 1 to 2 snacks has been found to be associated with good diet quality [1], whereas skipping breakfast has been consistently found to associate with poor overall diet quality and exposure to weight gain [2,3]. In addition, eating less than 3 times a day negatively influences appetite control, and unplanned snacking and consumption of the major part of the energy at the end of the day seem unfavorable for weight balance [4,5]. ...
... The measured attitudes and motives remained unchanged except for a small increase in weight control motive among the participants of Contentment group. To sum up, the study results indicate that self-monitoring of eating occasions with an EMA tool might assist in battling against the growing tendency of irregular eating [9][10][11][12][13] and harms related to it [2,3,[6][7][8]. The tool might be useful especially for people who follow a grazing eating pattern with no clear meal times but frequent peaks of eating occasions during the day. ...
Background: Temporal aspects of eating are an integral part of healthy eating, and regular eating has been associated with good diet quality and more successful weight control. Unfortunately, irregular eating is becoming more common. Self-monitoring of behavior has been found to be an efficient behavioral change technique, but the solution should be simple enough to ensure long-lasting adherence. Objective: This study aimed to explore the influence of self-monitoring of daily eating pattern with mobile phone app on eating rhythm, eating behavior tendencies, and the underlying motives and attitudes related to eating. Methods: A mobile phone app, Button, was developed for effortless self-monitoring of eating rhythm. The feasibility of the app was tested in a 30-day intervention. The participants (N=74) recorded their eating occasions during the intervention by pressing a button in the app widget. Results: The average interval between meals increased (96 [SD 24] min during the first 10 days vs 109.1[SD 36.4] during the last 10 days) and the number of daily eating occasions decreased (4.9 [SD 0.9] during the first 10 days vs 4.4 [SD 0.9] during the last 10 days). The tendencies for cognitive restraint, emotional eating, and uncontrolled eating increased. Eating-related attitudes and motives remained largely unchanged. Conclusions: These results indicate that a simple self-monitoring tool is able to draw a user’s attention to eating and is a potential tool to aid people to change their eating rhythm. © Saara Pentikäinen, Hannu Tanner, Leila Karhunen, Marjukka Kolehmainen, Kaisa Poutanen, Kyösti Pennanen.
... Breakfast skipping is associated with an increased risk of weight gain and obesity in young adults [8,9] as well as elevated cholesterol levels, overeating, and poor blood glucose control [6,10]. Yet, nearly 40% of American adults skip breakfast on any given day [11], despite the proven health benefits associated with eating breakfast such as increased feelings of fullness, reduced post-meal cravings [12][13][14][15][16][17], improved body composition [18], and a decreased incidence of overweight and obesity [6,19]. However, due to the lack of long-term randomized controlled trials, a strong link between breakfast skipping and health risk has not been established [8,16]. ...
... A majority of the breakfast literature is composed of acute meal studies, which make it difficult to make conclusions about the longer-term effects of breakfast interventions [11,[16][17][18]20]. Interestingly, just consuming breakfast in the morning has been shown to only transiently suppress appetite (i.e., 1-5 h) compared to skipping breakfast, without any difference over the remaining-hour period [9]. ...
The purpose of this study was to determine if breakfast macronutrient composition improved thermic effect of feeding (TEF) and appetite after a one-week adaptation in young women who habitually skip breakfast. A randomized, controlled study was conducted in females (24.1 ± 2 years), who skip breakfast (≥5 times/week). Participants were placed into one of three groups for eight days (n = 8 per group): breakfast skipping (SKP; no breakfast), carbohydrate (CHO; 351 kcal; 59 g CHO, 10 g PRO, 8 g fat) or protein (PRO; 350 kcal; 39 g CHO, 30 g PRO, 8 g fat). On days 1 (D1) and 8 (D8), TEF, substrate oxidation, appetite and blood glucose were measured. PRO had higher (p < 0.05) TEF compared to SKP and CHO on D1 and D8, with PRO having 29% higher TEF than CHO on D8. On D1, PRO had 30.6% higher fat oxidation than CHO and on D8, PRO had 40.6% higher fat oxidation than CHO. SKP had higher (p < 0.05) fat oxidation on D1 and D8 compared to PRO and CHO. There was an interaction (p < 0.0001) of time and breakfast on appetite response. In addition, CHO had a significant increase (p < 0.05) in PP hunger response on D8 vs. D1. CHO and PRO had similar PP (postprandial) glucose responses on D1 and D8. Consumption of PRO breakfast for 8 days increased TEF compared to CHO and SKP, while consumption of CHO for one week increased PP hunger response.
... 1,17,18 After the initialization of NES, it takes time to gain weight, so the relationship between BMI and NES may not be noticeable in young individuals. [19][20][21] In the present study, there was no relationship between NES and BMI, as previously stated in studies. [13][14][15] Similar to our results, higher average weight values of diagnostic NES participants can experience elevated BMI and obesity later in life, proven by researches thus, establishing risk factors for systemic diseases. ...
... There is an increasing rate of young adults who skip breakfast (Gwin and Leidy, 2018). Recent data indicates that many adults skip breakfast (McCrory, 2014;Neumann et al., 2016;Song et al., 2005) with, on average, up to 40% of adults skipping everyday (Neumann et al., 2016). Despite the known benefits of breakfast eating, Australian data on breakfast eating rates is lacking (Smith et al., 2017) and understanding of factors influencing breakfast eating is limited. ...
Purpose
The purpose of this study is to respond to calls to increase levels of theory application and extend understanding beyond individuals ensuring social and structural environmental considerations are taken into account. Social cognitive theory (SCT) was applied across two settings to examine its potential to explain breakfast eating frequency.
Design/methodology/approach
A cross-sectional survey was conducted in two institutional feeding populations [military ( n = 314) and mining ( n = 235)]. Participants reported key SCT constructs including breakfast eating behaviour (self-efficacy, skills, practice), cognitive aspects (knowledge, attitude, expectations) and their perceptions regarding environmental constructs (access, social norms, influence). These were measured and analysed through SPSS and structural equation modelling (SEM).
Findings
Results indicated that 71% males and 90% females in the military do not eat breakfast at work, and in the mining, 23% males and 24% of females do not eat breakfast at work. Furthermore, SEM modelling found only a satisfactory fit for SCT as operationalised in this study. Within the models, behavioural aspects of self-efficacy, skills and practice were significant influences on breakfast eating. Cognitive influences and perceptions of environmental influences exerted little to no effect on breakfast eating. Study results indicate that SCT, as measured in this study using a selection of environment, cognitive and behavioural constructs, does not offer sufficient explanatory potential to explain breakfast eating behaviour.
Originality/value
The value of this paper is to deliver a complete application of Social Cognitive Theory, ensuring multiple constructs are measured to examine the explanatory behaviour of breakfast eating frequency in workplace institutional settings.
... Amerika'da yapılan benzer bir çalışmada da 40-60 yaş arasındaki kadınların en sık öğle öğününü atladığı belirlenmiştir. 27 Bu araştırmada, ev hanımı olan kadınların oranının yüksek olması, kahvaltının geç saatte yapılıyor olduğunu düşündürmektedir. Bu durum, öğle öğününün atlanmasına neden olabilir. ...
... A systematic review including 36 cross-sectional and 9 cohort studies verified that skipping breakfast increased the risk of overweight/obesity [12]. Few studies have reported the clinical impact of lunch and dinner frequency on overweight/obesity [13,14], partly because a very low percentage of adults skip dinner [15]. ...
Although multiple studies have identified skipping breakfast as a risk factor for weight gain, there is limited evidence on the clinical impact of skipping lunch and dinner on weight gain. This retrospective cohort study including 17,573 male and 8860 female university students at a national university in Japan, assessed the association of the frequency of breakfast, lunch, and dinner with the incidence of weight gain (≥10%) and overweight/obesity (body mass index ≥ 25 kg/m2), using annual participant health checkup data. Within the observation period of 3.0 ± 0.9 years, the incidence of ≥10% weight gain was observed in 1896 (10.8%) men and 1518 (17.1%) women, respectively. Skipping dinner was identified as a significant predictor of weight gain in multivariable-adjusted Poisson regression models for both men and women (skipping ≥ occasionally vs. eating every day, adjusted incidence rate ratios, 1.45 (95% confidence interval: 1.04–2.01) and 1.67 (1.33–2.09) in male and female students, respectively), whereas skipping breakfast and lunch were not. Similarly, skipping dinner, not breakfast or lunch, was associated with overweight/obesity (1.74 (1.07–2.84) and 1.68 (1.02–2.78) in men and women, respectively). In conclusion, skipping dinner predicted the incidence of weight gain and overweight/obesity in university students.
... We conducted several sensitivity analyses and found that the results did not materially change when we excluded women with prevalent diabetes or hypertension at baseline (PR: 0.94; 95% CI: 0.88, 1.00; P-trend = 0.02); different categories of breakfast frequency, 6-7 d/wk compared to 0-1 d/wk (PR: 0.95; 95% CI: 0.91, 1.00; P-trend = 0.03); and weight gain ≥3 kg as the outcome (PR: 0.94; 95% CI: 0.88, 0.99; P-trend < 0.0001). Even if skipping breakfast may affect energy intake (34,35) and energy-adjustment may result in mediator bias, we conducted additional analyses adjusting for total energy. No substantial changes were observed after energy adjustment (PR: 0.93; 95% CI: 0.88, 0.99). ...
Background
Food timing affects circadian rhythms involved in weight control. Regular consumption of breakfast may affect body weight.
Objective
We examined the relation between breakfast frequency with weight change in middle-age women over a 3-y period.
Methods
We used data from 65,099 nonpregnant women aged >20 y participating in the Mexican Teachers’ Cohort (MTC) who at baseline (2006–2008) were cancer free and for whom self-reported breakfast frequency at baseline was available. We analyzed body weight change between baseline and the first follow-up (2011) according to breakfast frequency. Participants were classified according to baseline breakfast frequency 0, 1–3, 4–6, or 7 d/wk and meal frequency 1–2, 3–4, or ≥5 meals/d. We used linear and modified Poisson regression to analyze body weight change as a continuous variable and for weight gain ≥5 kg (yes/no), respectively. Models were adjusted for sociodemographic and lifestyle confounders.
Results
At baseline, 25% of participants were daily breakfast consumers and 18.4% of women increased ≥5 kg between 2008 and 2011. The prevalence of weight gain ≥5 kg among daily breakfast consumers was 7% lower than among those who skipped breakfast (prevalence ratio: 0.93; 95% CI: 0.89, 0.97; P-trend = 0.02). The association was stronger among normal-weight women at baseline with a corresponding estimate of 0.87 (95% CI: 0.79, 0.97; P-trend = 0.02).
Conclusion
Daily breakfast consumption was inversely associated with weight gain ≥5 kg over 3 y in middle-aged Mexican women. Regular breakfast may be an important dietary factor for body weight change.
... A quality breakfast should provide energy (about 25% of the total energy intake of the day) and nutrients according to daily needs, and has to be accessible and affordable [1,7]. This may help prevent chronic diseases like overweight, obesity, and diabetes [8], and others such as eating disorders, particularly binges [9]. ...
Skipping breakfast might have an impact on cognitive functions, such as interference, which is a basic capacity of executive functions that denotes the possibility of controlling an automated response. This study aimed to analyze the association between nutritional quality of breakfast and cognitive interference in a sample of university students. A cross-sectional study was conducted, a total of 422 students between 18 and 25 years participated. Cognitive interference was assessed with the Stroop Test. Breakfast was assessed with a questionnaire assigning a score for each serving of each food group that was consumed. Logistic regression models were performed. The performance in cognitive tasks was slower in those who had a poor breakfast (32.9 ± 6 vs 29.3 ± 6 s, p < 0.050). Poor cognitive interference was greater in students with poor breakfast (53% versus 23%, p = 0.001). A slower word reading was associated with skipping vegetables (OR: 2.78, 95% CI: 0.09-2.13), and cereals (OR: 1.70, 95% CI: 1.03-2.81). Wrong color identification was associated with skipping fruits (OR: 1.55, 95% CI: 1.43-1.99) and animal protein sources (OR: 1.63, 95% CI: 1.07-2.49). Skipping fat-rich cereals was a protector factor (OR: 0.55, 95% CI: 0.36-0.85). Difficulty in the ability to inhibit interference was associated with skipping vegetables (OR: 2.72, 95% CI: 1.25-4.80) and cereals (OR: 2.65, 95% CI: 1.28-4.68). The nutritional quality of breakfast was associated with the time spent answering the Stroop test, but not with cognitive interference.
... Subjective appetite variables such as "sensations of hunger, desire to eat, and prospective consumption" are estimated as higher in breakfast skipping comparing with breakfast eating conditions. Studies show that lunch intake was higher after breakfast skipping [40][41][42][43]. During 2015, two studies conducted by Clayton et al. [44,45] where the breakfast representing 25% energy supplies was taken at 08:00 clock, and lunch and dinner meals at 12:30 and 18:00-19:00 clock, respectively. ...
Breakfast, the first meal of the day, is considered the most important meal throughout the day. As nutritionist Adelle Davis famously put it back in the 1960s: “Eat breakfast like a king, lunch like a prince and dinner like a pauper”. Breakfast is most commonly skipped meal more than lunch and dinner specifically in the young adult in the university study period and those who wake up late. Lack of time is the main reason behind skipping meals, in general, lack of appetite, inability to cook, fasting/religion, and not being hungry. Many people are used to be in a hurry for job, business, children’s’ school in the morning where a filled stomach may prevent them to walk a long way. It is obvious that the irregular omission of breakfast may be effective in energy intake reduction over the next 24 hours and in this day, exercise performance may be compromised. There is no evidence that breakfast skipping reduces overeating or prevent weight gain. Some people argue that breakfast and good health is a marketing strategy by breakfast companies.
... Subjective appetite variables such as "sensations of hunger, desire to eat, and prospective consumption" are estimated as higher in breakfast skipping comparing with breakfast eating conditions. Studies show that lunch intake was higher after breakfast skipping [40][41][42][43]. During 2015, two studies conducted by Clayton et al. [44][45] where the breakfast representing 25% energy supplies was taken at 08:00 clock, and lunch and dinner meals at 12:30 and 18:00-19:00 clock, respectively. ...
... of the type of breakfast treatment or breakfast skipping interfering on energy intake and weight change. 47,57 For example, in the Bath Breakfast Project, daily breakfast was related to greater dietary energy intake among lean adults, 58 and more recent results from the same project with obese adults observed that breakfast skipping was related to partial greater energy intake later in the day. 59 The fact that the study sample was comprised of students from Rio de Janeiro metropolitan area can be considered as another limitation of the study because of its limited geographical scope. ...
Background:
The relationship between breakfast and family breakfast and adiposity gain during adolescence remains inconclusive.
Objective:
This study aimed to investigate the relationship between breakfast and family breakfast frequency and adiposity trajectory in adolescence.
Design:
Prospective cohort study with middle school students aged 10 to 16 years enrolled in 2010 (baseline) and followed for 3 years.
Participants/setting:
A total of 945 students from two public and four private schools in the metropolitan area of Rio de Janeiro were included. Among 945 students, 809 participated in the study at baseline. Pregnant or lactating students and those with physical or mental disabilities were excluded.
Main outcome measures:
Body mass index (BMI) was assessed by measuring the participants' weight and height, and percent body fat (%BF) was assessed by performing bioelectrical impedance analysis.
Statistical analyses performed:
Linear mixed-effect models were used to examine the relationship between baseline and persistence of breakfast consumption and family breakfast over a 3-year period and change in BMI and %BF. Breakfast and family breakfast were assessed by questions on frequency of consumption. Both variables were classified as regular, intermediate, and no consumption at baseline. Persistence was divided into persistently regular, persistently irregular, changing from regular to irregular, and contrariwise.
Results:
Overall, frequent breakfast consumption and family breakfast did not have protective effects against adiposity. At baseline, these behaviors were associated with low BMI and %BF among girls. During follow-up, these behaviors and persistence of regular breakfast consumption were associated with an increase in %BF (P<0.05). In boys, those who increased or decreased family breakfast frequency had greater decrease in %BF compared with those persistently regular at both time points.
Conclusion:
Breakfast had no consistent relationship with adolescence adiposity trajectory, which is in line with the results of experimental studies and in contrast with those of many cross-sectional studies.
... Subjective appetite variables such as "sensations of hunger, desire to eat, and prospective consumption" are estimated as higher in breakfast skipping comparing with breakfast eating conditions. Studies show that lunch intake was higher after breakfast skipping [40][41][42][43]. During 2015, two studies conducted by Clayton et al. [44][45] where the breakfast representing 25% energy supplies was taken at 08:00 clock, and lunch and dinner meals at 12:30 and 18:00-19:00 clock, respectively. ...
Breakfast, the first meal of the day, is considered the most important meal throughout the day. As nutritionist Adelle Davis famously put it back in the 1960s: "Eat breakfast like a king, lunch like a prince and dinner like a pauper". Breakfast is most commonly skipped meal more than lunch and dinner specifically in the young adult in the university study period and those who wake up late. Lack of time is the main reason behind skipping meals, in general, lack of appetite, inability to cook, fasting/religion, and not being hungry. Many people are used to be in a hurry for job, business, children's school in the morning where a filled stomach may prevent them to walk a long way. It is obvious that the irregular omission of breakfast may be effective in energy intake reduction over the next 24 hours and in this day, exercise performance may be compromised. There is no evidence that breakfast skipping reduces overeating or prevent weight gain. Some people argue that breakfast and good health is a marketing strategy by breakfast companies.
... However, conflicting results have been reported [6][7][8] , probably because definitions of breakfast and BS have not been established yet [9,10] . Multiple confounding factors, including age, sex, morbidities, and dietary culture, may also affect the outcomes, although these confounders are usually statistically adjusted for. ...
Traditionally, breakfast skipping (BS), and recently latenight
dinner eating (LNDE), have attracted attention
in public health because they can predispose to cardiometabolic
conditions such as obesity and type 2
diabetes. Intriguingly, it has become evident that
short duration of sleep elicits similar health risks. As
LNDE, BS, and short sleep can be closely related and
can aggravate each other, these three should not be
considered separately. In this context, LNDE (or its
equivalents, snacking or heavy alcohol consumption
after dinner) and BS may be representative unhealthy
eating habits around sleep (UEHAS). While it is
important to take energy in the early morning for
physical and intellectual activities, attaining a fasting
state is essential for metabolic homeostasis. Our
previous UEHAS studies have shown that BS without
LNDE, i.e. , BS alone, is not associated with obesity and
diabetes, suggesting the possibility that BS or taking
a very low energy breakfast, which could yield fasting
for a while, may prevent obesity and diabetes in people
with inevitable LNDE. Further studies considering
UEHAS and short sleep simultaneously are needed to
elucidate the effects of these unhealthy lifestyles on
cardiometabolic diseases.
... Eating rhythm is an integral part of healthy eating. A regular eating pattern including breakfast, lunch, dinner and 1-2 snacks has been found to be associated with good diet quality [1] while skipping breakfast has been consistently found to associate with poor overall diet quality and exposure to weight gain [2,3]. Irregular eating has been recently associated with various adverse health effects [4] as it may complicate weight regulation via hindered circadian system [5]. ...
BACKGROUND
Temporal aspects of eating are an integral part of healthy eating, and regular eating has been associated with good diet quality and more successful weight control. Unfortunately, irregular eating is becoming more common. Self-monitoring of behavior has been found to be an efficient behavioral change technique, but the solution should be simple enough to ensure long-lasting adherence.
OBJECTIVE
This study aimed to explore the influence of self-monitoring of daily eating pattern with mobile phone app on eating rhythm, eating behavior tendencies, and the underlying motives and attitudes related to eating.
METHODS
A mobile phone app, Button, was developed for effortless self-monitoring of eating rhythm. The feasibility of the app was tested in a 30-day intervention. The participants (N=74) recorded their eating occasions during the intervention by pressing a button in the app widget.
RESULTS
The average interval between meals increased (96 [SD 24] min during the first 10 days vs 109.1[SD 36.4] during the last 10 days) and the number of daily eating occasions decreased (4.9 [SD 0.9] during the first 10 days vs 4.4 [SD 0.9] during the last 10 days). The tendencies for cognitive restraint, emotional eating, and uncontrolled eating increased. Eating-related attitudes and motives remained largely unchanged.
CONCLUSIONS
These results indicate that a simple self-monitoring tool is able to draw a user’s attention to eating and is a potential tool to aid people to change their eating rhythm.
... Conversely, copious cross-sectional studies showed that people who skipped breakfast regularly had higher body mass index. [34] A few studies also report that skipping meals was more common among young adults. [35] An increase in the frequency of eating outside home has been considered as one of the factors which may contribute to the upsurge of obesity prevalence. ...
Background: Maladaptive eating behaviors and eating disorders are major determinants of overweight and obesity. Environment and urbanization exert tremendous effect on eating behaviors in population. Objective: The present study aims to identify prevalence of eating behaviors and eating disorders and their association to body weights among adult men and women in an urban region of south India. Method: This was a quantitative observational study. Men (107) and women (193) aged 27 to 47 years having BMI varying between 18.5 and 40 participated. Selection was based on purposive sampling method. Demographic details were obtained and eating behaviors and eating disorders were assessed using appropriate questionnaires. Height and weight of all the participants was obtained using standard techniques. Results: Our results demonstrated significant positive influence of eating patterns on body weight status, especially non-vegetarian diet practice, munching, number of meals consumed per day, meal skipping, eating outside home, high-fat eating and snacking. Munching(31% females, 35% males) was a common practice. Binge eating, picky eating, night eating, restrained eating and uncontrolled eating was found in less than 10% of the population. Emotional eating and food cravings were prevalent in markedly higher percentage of participants and were significantly associated with overweight and obesity (P<0.05). Conclusion: It is evident from the study that eating practices and eating disorders prevalent were essentially similar to those in developed countries. Occurrences of these eating disorders are indicative of the risk for an increase in overweight and obesity among population from underdeveloped countries.
... Regarding another question included in the Factor 2 group ("Healthy Factor"), related to Meal skipping and snacking ("Do You Skip Meals and Replace Them With Snacks?"), it must be noted that meal skipping and replacing meals by snacks is not a healthy behaviour. Indeed, not doing these actions is associated with healthier dietary habits, and relates to energy balance and micronutrient adequacy [51,52]. Thus this item was included but with the score inversely coded, giving the highest score in this item to those subjects who never or almost never skip meals. ...
Background
National guidelines emphasize healthy eating to promote wellbeing and prevention of non-communicable diseases. The perceived healthiness of food is determined by many factors affecting food intake. A positive perception of healthy eating has been shown to be associated with greater diet quality. Internet-based methodologies allow contact with large populations. Our present study aims to design and evaluate a short nutritional perception questionnaire, to be used as a screening tool for assessing nutritional status, and to predict an optimal level of personalisation in nutritional advice delivered via the Internet. Methods
Data from all participants who were screened and then enrolled into the Food4Me proof-of-principle study (n = 2369) were used to determine the optimal items for inclusion in a novel screening tool, the Nutritional Perception Screening Questionnaire-9 (NPSQ9). Exploratory and confirmatory factor analyses were performed on anthropometric and biochemical data and on dietary indices acquired from participants who had completed the Food4Me dietary intervention (n = 1153). Baseline and intervention data were analysed using linear regression and linear mixed regression, respectively. ResultsA final model with 9 NPSQ items was validated against the dietary intervention data. NPSQ9 scores were inversely associated with BMI (β = −0.181, p < 0.001) and waist circumference (Β = −0.155, p < 0.001), and positively associated with total carotenoids (β = 0.198, p < 0.001), omega-3 fatty acid index (β = 0.155, p < 0.001), Healthy Eating Index (HEI) (β = 0.299, p < 0.001) and Mediterranean Diet Score (MDS) (β = 0. 279, p < 0.001). Findings from the longitudinal intervention study showed a greater reduction in BMI and improved dietary indices among participants with lower NPSQ9 scores. Conclusions
Healthy eating perceptions and dietary habits captured by the NPSQ9 score, based on nine questionnaire items, were associated with reduced body weight and improved diet quality. Likewise, participants with a lower score achieved greater health improvements than those with higher scores, in response to personalised advice, suggesting that NPSQ9 may be used for early evaluation of nutritional status and to tailor nutritional advice. Trial registrationNCT01530139.
... It is possible that physical activity and age may have played a role in maintaining BMI among our students as most of them reported engaging in moderate/vigorous activities and were relatively young. Also, it is possible that age moderates the relationship between night eating and BMI as weight gain may only occur after longer periods of night eating; thus, in younger adults such as students there was no or only little relationship between NES and BMI [13,[56][57][58]. Therefore, the students complying with symptoms consistent with the proposed diagnostic criteria for any level of NES could experience elevated BMI later in life. ...
Background:
Night eating syndrome (NES) is characterized by evening hyperphagia and/or nocturnal ingestion.
Objective:
The main objective of this study was to assess the percentage of students complying with symptoms and behaviors consistent with the diagnostic criteria for NES, and explore its association with body mass index (BMI), dietary habits, physical activity, smoking status, and sleep patterns, among a sample of college students.
Methods:
A cross-sectional survey was conducted among a sample of 413 undergraduate students, mean age of 20.6 ± 1.68 SD, at Central Michigan University. Students completed an online survey including demographic information and the Night Eating Diagnostic Questionnaire (NEDQ) and Pittsburgh Sleep Quality Index Questionnaire (PSQI). Participants were grouped based on self-reporting of the presence and frequency of night eating-related symptoms and behaviors related to the diagnostic criteria for NES as follows: normal, mild night eater, moderate night eater, and full-syndrome night eater. Pearson's Chi-squared, Student's t test, and Wilcoxon rank-sum test were used to test the association between students with and without any night eating behavior in relation to BMI, lifestyle variables, and sleep duration/quality.
Results:
Results showed that the proportion of students complying with symptoms and behaviors consistent with full-syndrome of NES was 1.2%. There were no significant differences between students complying with symptoms and behaviors consistent with any level of NES and those without any night eating behavior regarding BMI, eating habits, physical activity, and smoking status. NES was significantly related to sleep duration (P = 0.023). Students complying with symptoms consistent with any level of NES reported shorter sleep time and had higher total PSQI score (6.73 ± 4.06) than students without the syndrome (5.61 ± 2.61) (P = 0.007).
Conclusion:
Although the percentage of students complying with full-syndrome NES was relatively low in our student sample, those students had shorter sleep time and poorer sleep quality than the other groups. However, it is unclear whether evening hyperphagia is a response to a lack of sleep or vice versa, and further research is needed.
Level of evidence:
Level III, case-control analytic study.
... [10][11][12] Indeed, this may be an effective strategy to improve diet quality in young adults because the prevalence of breakfast skipping in this group has been reported between 22% and 37%. 5,13,14 In addition, multiple sources have suggested an association of meal patterns, including number of eating occasions and snacking frequency with diet quality. [15][16][17] Therefore, it is of interest to describe dietary intake by time of day and characterize the differences between breakfast eaters and skippers. ...
Background:
Previous studies suggest skipping breakfast is associated with lower diet quality, but possible reasons underlying this relationship are not clear.
Objective:
Our aim was to determine the relationship between chronic stress and variations in diet quality in the context of breakfast eating or breakfast skipping.
Design:
Based on morning eating habits, 40 breakfast eaters and 35 breakfast skippers participated in a cross-sectional study. Diet assessment was based on unannounced 24-hour recalls.
Participants/setting:
Women, ages 18 to 45 years, with a body mass index (calculated as kg/m(2)) <40 were recruited in the greater Sacramento, CA, area between 2009 and 2013. Only women who consistently ate or skipped breakfast were enrolled.
Main outcome measures:
Compliance with the 2010 Dietary Guidelines for Americans was measured using the Healthy Eating Index 2010 (HEI-2010). Stress and executive function were evaluated with validated questionnaires and a computer-based task, respectively.
Statistical analyses performed:
Diet characteristics of breakfast eating and breakfast skipping were evaluated as nutrient densities (amounts per 1,000 kcal) and compared using a one-way analysis of covariance, with body mass index as covariate. Diet and stress variable associations were assessed using Pearson correlations.
Results:
Despite no observed differences in daily energy intake between breakfast skipping and breakfast eating, overall diet quality (P=0.001), whole grains (P=0.002), fruit (P=0.002), empty calories (P=0.050), fiber (P=0.001), calcium (P=0.001), potassium (P=0.033), and folate (P=0.013) intakes were higher in breakfast eating. In the evening, breakfast skipping consumed more added sugars (P=0.012) and saturated fat (P=0.006). In breakfast skipping, reported stress was associated with empty calories (r=-0.39; P=0.027) and evening intake of added sugars (r=0.501; P=0.005). These relationships were not observed in breakfast eating.
Conclusions:
Breakfast skippers were less likely to meet the Dietary Guidelines for Americans and consumed more empty calories at night. Chronic stress was related to evening eating choices and overall empty calories in the diet of breakfast skippers, whereas breakfast eaters' dietary intake did not appear to be affected by chronic stress.
... Moreover, some studies have shown that skipping meals, especially breakfast, is associated with the risk of overweight and obesity in children [35] and adults [14]. This can also cause accumulation of fat in the abdominal area which increases the risk of metabolic syndrome [36]. Finally, skipping meals has been reported to be associated with increased appetite [34]. ...
Purpose:
Nutrition plays a major role in physical and mental health. The aim of this study was to evaluate the relationships between happiness and fruit and vegetable intake as well as eating breakfast in students.
Methods:
In this cross-sectional web-based study, all students of Qazvin University of Medical Sciences in Iran who attended course classes were invited to participate in the study. Five hundred forty-one students filled out the web-based questionnaire which included questions related to measurement of happiness, breakfast, fruit and vegetable consumption and socio-economic and demographic information. Analysis of covariance was used to assess the relationship between happiness and breakfast, fruit and vegetable consumption by adjustments for covariates.
Results:
Measure of happiness was positively associated with eating breakfast, number of meals eaten daily and the amount of fruit and vegetable consumption (P values were <0.001, 0.008, 0.02, and 0.045 respectively). Students who ate breakfast every day, more than 8 servings of fruit and vegetables daily, and had 3 meals in addition to 1-2 snacks per day had the highest happiness score.
Conclusion:
Healthier behavior pattern was associated with higher happiness scores among medical students.
... p=0.08 for the whole population and OR=0.3, p=0.05 for women). Previous studies have also shown that skipping meals [25], especially breakfast [26,27], is associated with the higher risk of overweight. More importantly, skipping meals may be associated with accumulation of adipose tissue in visceral areas and increased risk of metabolic diseases [28]. ...
Obesity is an epidemic nutritional disease caused mainly by excessive dietary intake and/or insufficient exercise. The purpose of this study was to investigate associations between a number of demographic characteristics and eating habits with prevalence of overweight and obesity in hospital employees. The study was cross-sectional performed on employees of Namazi Hospital in Shiraz, Iran. Subjects were selected from different departments of the hospital. Demographic characteristics, eating habits, and exercise were questioned by interview. Overweight and obesity was defined as a body mass index ≥ 25 kg/m 2. The rate of overweight/obesity was 30.2%. Among demographic characteristics, only age (OR=5.6 for older ages, p=0.001) and sex (OR=0.4 for females, p=0.04) were significantly associated with overweight/obesity. Skipping breakfast was not associated with overweight/obesity, but skipping meals (OR=2.8, p=0.08) and consuming ≥ 3 snacks per day (OR=0.2, p=0.05) had associations with it, although non-significantly. Performing ≥ 60 min/day (but not ≥ 45 min/day) exercise was associated with a lower risk of overweight/obesity (OR=0.1, p=0.01). The association between exercise and overweight/obesity existed in both sexes, but the association between skipping meals and obesity was present only in females (OR=3.8, p=0.05). Females skipped meals especially breakfast more frequently than males (p=0.001) but snack consumption and exercise was not statistically different between the two sexes. Eating 3 meals and at least 3 snacks per day and performing 1 hour or more exercise may be introduced as helpful strategies in prevention of obesity.
... Timing of eating events has been suggested as one factor of the multifactorial etiology of obesity [64••]. Longitudinal studies suggest that skipping breakfast may play one potential role in weight gain, although a few experimental studies showed mixed results [65,66]. In a cross-sectional study, Wang et al. showed that consuming more in the evening was associated with a higher risk for obesity, while eating more of the total daily intake at midday was associated with lower risk [67]. ...
This review focuses on the influence of portion size and temporal distribution of food intake on weight balance and obesity in adults. The inconsistency of definitions in the area of meal patterns is also discussed. The conclusion is that regular eating habits might facilitate weight balance, while unplanned snacking as well as consuming the major part of the energy intake at the end of the day seem to be unfavourable. Altogether, the research suggests that large portions promote over-consumption and, therefore, limiting portion size of energy dense foods and drinks with added sugar could be recommended. Even if more research is needed, these factors should be taken into consideration in recommendations for obesity prevention.
Behçet hastalığı (BH)'nda beslenme alışkanlıklarının, besin tüketimlerinin yeterlilik durumunun ve depresyon düzeyinin belirlenmesidir. Gereç ve Yöntemler: Araştırmaya Aralık 2018-Mayıs 2019 tarihleri arasında bir üniversite hastanesinin Behçet polikliniğine başvuran, hastalığı aktif/inaktif durumdaki BH'li 62 hasta ile yaş ve cinsiyet bakımından hastalarla benzer özellikler taşıyan 48 sağlıklı birey dâhil edilmiştir. Çalışmanın etik kurul izinleri alınmış, veriler yüz yüze görüşme yöntemiyle literatürden yararlanılarak hazırlanan anket formuyla toplanmıştır. Besin tüketimlerinin belirlenmesi için 24 saatlik hatırlatma yöntemi ile depresyon düzeyinin belirlenmesi için de Beck Depresyon Ölçeği kullanılmıştır. Verilerin analizinde; ortalama, standart sapma, t-testi ve Pearson korelasyon testi kullanılmıştır. Bulgular: BH'lilerin %37,1'inin günde 2 öğün beslendiği ve en çok atlanan öğünün ise öğle yemeği (%73,5) olduğu saptanmıştır. Hastaların ekmek ve tahıl grubu haricinde diğer besin gruplarından tükettikleri porsiyon miktarlarının sağlıklı bireylerden daha düşük olduğu ve hastaların günlük enerjilerinin yağdan gelen kısmının %37,2±7,74 olduğu belirlenmiştir. BH'lilerin %95,22sinin günlük önerilen referans değerlerin altında süt ve süt ürünleri grubu ile meyveler grubundaki besinlerden tükettiği bulunmuştur. Ayrıca BH'lilerde depresyon puanının (13,5±9,81), sağlıklı bireylerden (8,1±7,44) önemli düzeyde yüksek olduğu ve hastaların %32,3'ünde orta ve şiddetli depresyon semptomları bulunduğu saptanmıştır. Sonuç: Behçet Hastalarının yeterli ve dengeli beslenmedikleri ve depresyon düzeyinin yüksek olduğu, bu nedenle hastalarda ek fizyolojik ve psikiyatrik hastalıkların gelişme riskinin arttığı belirlenmiştir.
The aim of this study was to examine various psychosocial, behavioral, and socio-environmental factors in a multiethnic sample of healthy-weight, overweight, and obese youths in the United States (US) and Mexico and determine differences by sex. We conducted a cross-sectional analysis of 633 youths aged 11–18 years who completed a self-reported questionnaire. Height and weight were measured to determine body mass index (BMI). Overweight and obese youth in both countries were significantly more likely to report a higher body image dissatisfaction (Odds Ratio (OR) = 1.67 and OR= 2.95, respectively), depressive symptoms (OR = 1.08 and OR = 1.12, respectively), perceive themselves as overweight (OR = 2.57) or obese (OR = 5.30), and a lower weight-specific quality of life (OR = 0.97 and OR = 0.95, respectively) than healthy-weight youth. Obese youth have lower healthy lifestyle priorities (OR = 0.75) and are less likely to be physically active (OR = 0.79) and eat breakfast (OR = 0.47) than healthy-weight youth. Additionally, overweight and obese youth are more likely to engage in weight control behaviors (OR = 5.19 and OR = 8.88, respectively) and restrained eating than healthy-weight youth. All the aforementioned results had a p-value of <0.05, which was considered statistically significant. The association between these factors and overweight or obesity remained significant after controlling for age, sex, race/ethnicity, and country. In conclusion, obesity was associated with a range of psychosocial, behavioral, and socio-environmental risk factors in both countries. Our findings support the need for multifactorial approaches when developing interventions to address the growing problem of obesity among youth in the US and Mexico.
Breakfast skipping is associated with increased risk of weight gain and obesity in young adults, possibly due to increased snacking later in the day. Recent research suggests that providing and animal versus a plant source of protein at breakfast can reduce snack intake later in the day. In addition, providing nutrition information via a nutrition label, front-of-pack information, or via text messaging has been shown to help individuals make healthier food choices. The objective of this study was to determine if educational nutrition messaging and protein source influenced snack intake two hours following the breakfast meal. Participants (n = 33) were randomly assigned to one of two groups: educational nutrition messaging (EM; n = 16) or no messaging (NM; n = 17) group. The study was conducted using a randomized, cross-over design in which each participant received each of two breakfast beverages, whey protein- (WP) and pea protein (PP)- based. Appetite was assessed at 0, 15, 30, 60, 90, and 120 min after each test breakfast using visual analog scales. Participants were then provided with a selection of healthy and unhealthy snacks for 60 min. There was no effect of protein source on appetite or snack intake. However, participants presented with EM had reduced snack intake over the snacking period compared to NM (P = 0.058) and, of the snacks consumed, the EM group consumed a higher percentage of healthy versus unhealthy snacks compared to NM (P < 0.0001), resulting in lower calorie intake. Taken together these data suggest that protein source, as part of a higher protein breakfast, does not affect appetite response or snack intake, but EM may help play a role in reducing snack intake between meals.
Understanding the determinants of obesity and developing appropriate prevention and treatment strategies require an in-depth examination of behavioral risk factors for obesity. The goal of this chapter is to review available data regarding the prevalence of overweight and obesity and the modifiable dietary and physical activity behavioral determinants of obesity that are potential targets for obesity prevention and treatment interventions. We begin with an examination of dietary factors that contribute to the development of overweight and obesity. Multiple factors that influence food intake will be discussed, including total energy intake, specific eating patterns, and environmental and societal influences. We then discuss physical activity factors, including exercise self-efficacy, social support, and access to exercise opportunities. The review will focus on behavioral risk factors for obesity in both children and adults.
The effect of different breakfast consumption patterns on nutrient intake, diet quality, and weight/adiposity status is unknown.
To compare nutrient intake, diet quality, and weight/adiposity measures of consumers assigned to different breakfast patterns with breakfast skippers.
These associations were assessed in adults 19+ years (N=18,988) participating in the 2001-2008 National Health and Nutrition Examination Survey. Intake was determined from 1-day 24-hour dietary recall. Diet quality was quantified using the Healthy Eating Index-2005. Body mass index (calculated as kg/m(2)) and waist circumferences were determined. Twelve patterns (including No Breakfast [approximately 19% of population]), explaining 58% of the variance in energy from the breakfast meal, were examined. Covariate adjusted general linear models were used to compare nutrient intakes, Healthy Eating Index-2005 scores, and body mass index/waist circumference of consumers of different patterns with breakfast skippers. The P value was Bonferroni corrected (<0.05/12 breakfast patterns <0.0042).
Consumers of the Grain/100% Fruit Juice and Presweetened Ready-to-Eat Cereal (RTEC)/Lower-Fat Milk patterns had lower daily intakes of nutrients to limit (added sugars, saturated fatty acids, solid fats, cholesterol, and sodium) than breakfast skippers. Consumers of the Grain/100% Fruit Juice; Presweetened RTEC/Lower-Fat Milk; and RTEC/Lower-Fat Milk/Whole Fruit/100% Fruit Juice patterns had higher daily intakes of all shortfall nutrients examined (dietary fiber; vitamins A, D, and C; calcium, potassium, folate, iron, and magnesium) than breakfast skippers. Consumers of the Grain/100% Fruit Juice; Grain; Presweetened RTEC/Lower-Fat Milk; RTEC/Lower-Fat Milk/Whole Fruit/100% Fruit Juice; Cooked Cereal; Lower-Fat Milk/Whole Fruit; and Whole Fruit patterns had higher Healthy Eating Index-2005 scores than breakfast skippers. Consumers of the Grain/100% Fruit Juice; Presweetened RTEC/Lower-Fat Milk; RTEC/Lower-Fat Milk/Whole Fruit/100% Fruit Juice; and Cooked Cereal patterns had lower body mass indexes and waist circumferences than breakfast skippers.
Results suggest dietary and weight advantages of consuming breakfast, especially ones that include grains, cereals, lower-fat milk, and whole fruit/100% fruit juice, in contrast to the potential adverse effects of skipping breakfast.
Copyright © 2014 Academy of Nutrition and Dietetics. Published by Elsevier Inc. All rights reserved.
OBJECTIVE
The relation of breakfast intake frequency to metabolic health is not well studied. The aim of this study was to examine breakfast intake frequency with incidence of metabolic conditions.RESEARCH DESIGN AND METHODS
Analysis of 3,598 participants from the community-based Coronary Artery Risk Development in Young Adults (CARDIA) study who were free of diabetes in the year 7 examination when breakfast and dietary habits were assessed (1992-1993) and participated in at least one of the five subsequent follow-up examinations over 18 years.RESULTSRelative to infrequent breakfast consumption (0-3 days/week), participants who reported eating breakfast daily gained 1.9 kg less weight over 18 years (P = 0.001). In a Cox regression analysis, there was a stepwise decrease in risk across conditions in frequent breakfast consumers (4-6 days/week) and daily consumers. The results for incidence of abdominal obesity, obesity, metabolic syndrome, and hypertension remained significant after adjustment for baseline measures of adiposity (waist circumference or BMI) in daily breakfast consumers. Hazard ratios (HRs) and 95% CIs for daily breakfast consumption were as follows: abdominal obesity HR 0.78 (95% CI 0.66-0.91), obesity 0.80 (0.67-0.96), metabolic syndrome 0.82 (0.69-0.98), and hypertension 0.84 (0.72-0.99). For type 2 diabetes, the corresponding estimate was 0.81 (0.63-1.05), with a significant stepwise inverse association in black men and white men and women but no association in black women. There was no evidence of differential results for high versus low overall dietary quality.CONCLUSIONS
Daily breakfast intake is strongly associated with reduced risk of a spectrum of metabolic conditions.
Background: Breakfast skipping is a common dietary habit practiced among adolescents and is strongly associated with obesity.
Objective: The objective was to examine whether a high-protein (HP) compared with a normal-protein (NP) breakfast leads to daily improvements in appetite, satiety, food motivation and reward, and evening snacking in overweight or obese breakfast-skipping girls.
Design: A randomized crossover design was incorporated in which 20 girls [mean ± SEM age: 19 ± 1 y; body mass index (in kg/m2): 28.6 ± 0.7] consumed 350-kcal NP (13 g protein) cereal-based breakfasts, consumed 350-kcal HP egg- and beef-rich (35 g protein) breakfasts, or continued breakfast skipping (BS) for 6 d. On day 7, a 10-h testing day was completed that included appetite and satiety questionnaires, blood sampling, predinner food cue–stimulated functional magnetic resonance imaging brain scans, ad libitum dinner, and evening snacking.
Results: The consumption of breakfast reduced daily hunger compared with BS with no differences between meals. Breakfast increased daily fullness compared with BS, with the HP breakfast eliciting greater increases than did the NP breakfast. HP, but not NP, reduced daily ghrelin and increased daily peptide YY concentrations compared with BS. Both meals reduced predinner amygdala, hippocampal, and midfrontal corticolimbic activation compared with BS. HP led to additional reductions in hippocampal and parahippocampal activation compared with NP. HP, but not NP, reduced evening snacking of high-fat foods compared with BS.
Conclusions: Breakfast led to beneficial alterations in the appetitive, hormonal, and neural signals that control food intake regulation. Only the HP breakfast led to further alterations in these signals and reduced evening snacking compared with BS, although no differences in daily energy intake were observed. These data suggest that the addition of breakfast, particularly one rich in protein, might be a useful strategy to improve satiety, reduce food motivation and reward, and improve diet quality in overweight or obese teenage girls. This trial was registered at clinicaltrials.gov as NCT01192100.
Background
Research suggests that the interaction between biological susceptibility and environmental risk is complex and that further study of behavioral typologies related to obesity and associated behaviors is important to further elucidate the nature of obesity risk and how to approach it for intervention. The current investigation aims to identify phenotypical lifestyle patterns that might begin to unify our understanding of obesity and obesity related behaviors.
Methods
Individuals who had recently lost substantial weight of their own initiative completed measures of intentional weight control behaviors and lifestyle behaviors associated with eating. These behaviors were factor analyzed and the resulting factors were examined in relation to BMI, recent weight loss, diet, and physical activity.
Results
Four meaningful lifestyle and weight control behavioral factors were identified— regularity of meals, TV related viewing and eating, intentional strategies for weight control, and eating away from home. Greater meal regularity was associated with greater recent weight loss and greater fruit and vegetable intake. Greater TV related viewing and eating was associated with greater BMI and greater fat and sugar intake. More eating away from home was related to greater fat and sugar intake, lower fruit and vegetable intake, and less physical activity. Greater use of weight control strategies was most consistently related to better weight, diet, and physical activity outcomes.
Conclusions
Compared to the individual behavior variables, the identified lifestyle patterns appeared to be more reliably related to diet, physical activity, and weight (both BMI and recent weight loss). These findings add to the growing body of literature identifying behavioral patterns related to obesity and the overall weight control strategy of eating less and exercising more. In future research it will be important to replicate these behavioral factors (over time and in other samples) and to examine how changes in these factors relate to weight loss and weight maintenance over time.
Excess bodyweight is a major public health concern. However, few worldwide comparative analyses of long-term trends of body-mass index (BMI) have been done, and none have used recent national health examination surveys. We estimated worldwide trends in population mean BMI.
We estimated trends and their uncertainties of mean BMI for adults 20 years and older in 199 countries and territories. We obtained data from published and unpublished health examination surveys and epidemiological studies (960 country-years and 9·1 million participants). For each sex, we used a Bayesian hierarchical model to estimate mean BMI by age, country, and year, accounting for whether a study was nationally representative.
Between 1980 and 2008, mean BMI worldwide increased by 0·4 kg/m(2) per decade (95% uncertainty interval 0·2-0·6, posterior probability of being a true increase >0·999) for men and 0·5 kg/m(2) per decade (0·3-0·7, posterior probability >0·999) for women. National BMI change for women ranged from non-significant decreases in 19 countries to increases of more than 2·0 kg/m(2) per decade (posterior probabilities >0·99) in nine countries in Oceania. Male BMI increased in all but eight countries, by more than 2 kg/m(2) per decade in Nauru and Cook Islands (posterior probabilities >0·999). Male and female BMIs in 2008 were highest in some Oceania countries, reaching 33·9 kg/m(2) (32·8-35·0) for men and 35·0 kg/m(2) (33·6-36·3) for women in Nauru. Female BMI was lowest in Bangladesh (20·5 kg/m(2), 19·8-21·3) and male BMI in Democratic Republic of the Congo 19·9 kg/m(2) (18·2-21·5), with BMI less than 21·5 kg/m(2) for both sexes in a few countries in sub-Saharan Africa, and east, south, and southeast Asia. The USA had the highest BMI of high-income countries. In 2008, an estimated 1·46 billion adults (1·41-1·51 billion) worldwide had BMI of 25 kg/m(2) or greater, of these 205 million men (193-217 million) and 297 million women (280-315 million) were obese.
Globally, mean BMI has increased since 1980. The trends since 1980, and mean population BMI in 2008, varied substantially between nations. Interventions and policies that can curb or reverse the increase, and mitigate the health effects of high BMI by targeting its metabolic mediators, are needed in most countries.
Bill & Melinda Gates Foundation and WHO.
Observational studies of breakfast frequency in children and adults suggest an inverse (protective) association between the frequency of eating breakfast and the risk for obesity and chronic diseases such as type 2 diabetes. More prospective studies with stronger designs are needed, as are experimental studies on this topic. In addition, above and beyond breakfast frequency, the roles of dietary quality and composition need to be studied in the context of eating or skipping breakfast. Experimental studies are also necessary to rigorously test causality and biological mechanisms. Therefore, we conducted 2 pilot experimental studies to examine some of the effects of breakfast skipping and breakfast composition on blood glucose and appetite in children and adults. Our results suggest that breakfast frequency and quality may be related in causal ways to appetite controls and blood sugar control, supporting the hypothesis that the breakfast meal and its quality may have important causal implications for the risk of obesity and type 2 diabetes.
Fifty-two moderately obese adult women were stratified according to their baseline breakfast-eating habits and randomly assigned a weight-loss program. The no-breakfast group ate two meals per day and the breakfast group ate three meals per day. The energy content of the two weight-loss programs was identical. After the 12-wk treatment, baseline breakfast eaters lost 8.9 kg in the no-breakfast treatment and 6.2 kg in the breakfast treatment. Baseline breakfast skippers lost 7.7 kg in the breakfast treatment and 6.0 kg in the no-breakfast treatment. This treatment-by-strata-by-time interaction effect (P less than 0.06) suggests that those who had to make the most substantial changes in eating habits to comply with the program achieved better results. Analyses of behavioral data suggested that eating breakfast helped reduce dietary fat and minimize impulsive snacking and therefore may be an important part of a weight-reduction program.
Breakfast consumption is recommended, despite inconclusive evidence of health benefits.
The study's aim was to ascertain whether eating breakfast (EB) or omitting breakfast (OB) affects energy intake, energy expenditure, and circulating insulin, glucose, and lipid concentrations in healthy women.
In a randomized crossover trial, 10 women [x+/-SD body mass index (BMI; in kg/m2): 23.2+/-1.4] underwent two 14-d EB or OB interventions separated by a 2-wk interval. In the EB period, subjects consumed breakfast cereal with 2%-fat milk before 0800 and a chocolate-covered cookie between 1030 and 1100. In the OB period, subjects consumed the cookie between 1030 and 1100 and the cereal and milk between 1200 and 1330. Subjects then consumed 4 additional meals with content similar to usual at predetermined times later in the day and recorded food intake on 3 d during each period. Fasting and posttest meal glucose, lipid, and insulin concentrations and resting energy expenditure were measured before and after each period.
Reported energy intake was significantly lower in the EB period (P=0.001), and resting energy expenditure did not differ significantly between the 2 periods. OB was associated with significantly higher fasting total and LDL cholesterol than was EB (3.14 and 3.43 mmol/L and 1.55 and 1.82 mmol/L, respectively; P=0.001). The area under the curve of insulin response to the test meal was significantly lower after EB than after OB (P<0.01).
OB impairs fasting lipids and postprandial insulin sensitivity and could lead to weight gain if the observed higher energy intake was sustained.
There is a general perception that almost no one succeeds in long-term maintenance of weight loss. However, research has shown that approximately 20% of overweight individuals are successful at long-term weight loss when defined as losing at least 10% of initial body weight and maintaining the loss for at least 1 y. The National Weight Control Registry provides information about the strategies used by successful weight loss maintainers to achieve and maintain long-term weight loss. National Weight Control Registry members have lost an average of 33 kg and maintained the loss for more than 5 y. To maintain their weight loss, members report engaging in high levels of physical activity ( approximately 1 h/d), eating a low-calorie, low-fat diet, eating breakfast regularly, self-monitoring weight, and maintaining a consistent eating pattern across weekdays and weekends. Moreover, weight loss maintenance may get easier over time; after individuals have successfully maintained their weight loss for 2-5 y, the chance of longer-term success greatly increases. Continued adherence to diet and exercise strategies, low levels of depression and disinhibition, and medical triggers for weight loss are also associated with long-term success. National Weight Control Registry members provide evidence that long-term weight loss maintenance is possible and help identify the specific approaches associated with long-term success.
To study changes in lifestyle in relation to changes in body weight and waist circumference associated with occupational retirement in men.
A prospective cohort study with 5 years of follow-up. At baseline and at follow-up, questionnaires were completed and body weight and waist circumference were measured.
The Doetinchem Cohort Study, consisting of inhabitants of Doetinchem, a town in a rural area of The Netherlands.Subjects: In total 288 healthy men aged 50-65 years at baseline, who either remained employed or retired over follow-up.
The effect of retirement on changes in weight and waist circumference was dependent on type of former occupation. Increase in body weight and waist circumference was higher among men who retired from active jobs (0.42 kg year(-1) and 0.77 cm year(-1), respectively) than among men who retired from sedentary jobs (0.08 kg year(-1) and 0.23 cm year(-1), respectively). Weight gain and increase in waist circumference were associated with a decrease in fruit consumption and fibre density of the diet, with an increase in frequency of eating breakfast, and with a decrease in several physical activities, such as household activities, bicycling, walking and doing odd jobs.
Retirement was associated with an increase in weight and waist circumference among those with former active jobs, but not among those with former sedentary jobs. Retirement may bring opportunities for healthy changes in diet and physical activity, which could be used in health promotion programmes.
The contributors to trends in increasing prevalence of obesity in the US population are poorly understood.
We examined secular trends in food consumption behaviors to understand their possible contribution to increasing energy intakes and adiposity in the American population.
We used dietary data from 4 consecutive National Health and Nutrition Examination Surveys (NHANES) to examine trends (1971-2002) in frequency of eating episodes, meal and snack consumption, quantity of food consumed, and the energy density of foods reported by adult Americans (n = 39 094). Logistic and linear regression methods were used to adjust for multiple covariates and survey design.
The reported number of all eating episodes increased slightly in women from 4.90 in 1971-1975 to 5.04 in 1999-2002 (P for trend = 0.002). The amount (in g) of foods and beverages consumed, the energy density of foods, and energy intake per eating episode increased, but the mention of breakfast declined in both sexes (P for trend < 0.0001). The observed trends in mention of a snack (in men) and percentage of energy from evening food intake (in women) were downward. The amount (in g) of foods and their energy density were independent positive correlates of obesity in combined data from all surveys (P for trend < 0.0001).
Our results do not support large increases in eating frequency, snacking, or evening eating by the American population from 1971 to 2002. The quantity of foods and their energy density increased beginning in NHANES III (1988-1994) with trajectories roughly parallel to the rates of prevalence of obesity in the US population. However, we urge cautious interpretation of these results because of concurrent changes in dietary methods during this period.
To investigate the association between percentage of total daily energy intake consumed at breakfast and weight change in middle-aged men and women, the authors analyzed data from a prospective population-based cohort study from Norfolk, United Kingdom. Participants were 6,764 men and women aged 40-75 years at baseline (1993-1997). Participants completed a 7-day food diary at baseline, and objective measurements of height and weight were carried out at baseline and follow-up (1998-2000). Mean baseline body mass index (weight (kg)/height (m)(2)) was lowest among persons in the highest quintile of percentage of daily energy consumed at breakfast (mean values were 26.0 in the highest quintile and 26.3 in the lowest quintile), despite higher daily total energy intake in this group. Although all participants gained weight, increased percentage of daily energy consumed at breakfast was associated with relatively lower weight gain (adjusted beta coefficient = -0.021, 95% confidence interval: -0.035, -0.007; p = 0.004). The association between percentage of daily energy intake consumed at breakfast and weight gain was independent of age, sex, smoking, total energy intake, macronutrient intake, social class, and physical activity. Redistribution of daily energy intake, so that more energy is consumed at breakfast and less energy is consumed later in the day, may help to reduce weight gain in middle-aged adults.
There is a general perception that almost no one succeeds in long-term maintenance of weight loss. However, research has shown that ≈20% of overweight individuals are successful at long-term weight loss when defined as losing at least 10% of initial body weight and maintaining the loss for at least 1 y. The National Weight Control Registry provides information about the strategies used by successful weight loss maintainers to achieve and maintain long-term weight loss. National Weight Control Registry members have lost an average of 33 kg and maintained the loss for more than 5 y. To maintain their weight loss, members report engaging in high levels of physical activity (≈1 h/d), eating a low-calorie, low-fat diet, eating breakfast regularly, self-monitoring weight, and maintaining a consistent eating pattern across weekdays and weekends. Moreover, weight loss maintenance may get easier over time; after individuals have successfully maintained their weight loss for 2–5 y, the chance of longer-term success greatly increases. Continued adherence to diet and exercise strategies, low levels of depression and disinhibition, and medical triggers for weight loss are also associated with long-term success. National Weight Control Registry members provide evidence that long-term weight loss maintenance is possible and help identify the specific approaches associated with long-term success.
Various intentional and unintentional factors influence beliefs beyond what scientific evidence justifies. Two such factors are research lacking probative value (RLPV) and biased research reporting (BRR).
We investigated the prevalence of RLPV and BRR in research about the proposition that skipping breakfast causes weight gain, which is called the proposed effect of breakfast on obesity (PEBO) in this article.
Studies related to the PEBO were synthesized by using a cumulative meta-analysis. Abstracts from these studies were also rated for the improper use of causal language and biased interpretations. In separate analyses, articles that cited an observational study about the PEBO were rated for the inappropriate use of causal language, and articles that cited a randomized controlled trial (RCT) about the PEBO were rated for misleadingly citing the RCT.
The current body of scientific knowledge indicates that the PEBO is only presumed true. The observational literature on the PEBO has gratuitously established the association, but not the causal relation, between skipping breakfast and obesity (final cumulative meta-analysis P value <10(-42)), which is evidence of RLPV. Four examples of BRR are evident in the PEBO literature as follows: 1) biased interpretation of one's own results, 2) improper use of causal language in describing one's own results, 3) misleadingly citing others' results, and 4) improper use of causal language in citing others' work.
The belief in the PEBO exceeds the strength of scientific evidence. The scientific record is distorted by RLPV and BRR. RLPV is a suboptimal use of collective scientific resources.
The objective was to examine the effect of consuming breakfast on subsequent energy intake. Participants who habitually ate breakfast and those who skipped breakfast were recruited for two studies. Using a randomized crossover design , the first study, examined the effect of having participants consume either (a) no breakfast, (b) a high carbohydrate breakfast (335 kcals) or (c) a high fiber breakfast (360) kcals on three occasions and measured ad libitum intake at lunch. The second study again used a randomized crossover design but with a larger, normal carbyhydrate, breakfast consumed ad libtum. Intake averaged 624 kcals and subsequent food intake was measured throughout the day.Participants ate only foods served from the Cornell Human Metabolic Research Unit where all foods were weighed before and after consumption. In the first study, neither eating breakfast nor the kind of breakfast consumed had an effect on the amount consumed at lunch despite a reduction in hunger ratings. In the second study, intake at lunch as well as hunger ratings was significantly increased after skipping breakfast, by 144 Kcal, leaving a net caloric deficit of 408 Kcal by the end of the day.These data are consistent with published literature demonstrating that skipping a meal does not result in accurate energy compensation at subsequent meals and suggests that skipping breakfast may be an effective means to reduce daily energy intake in some adults.
Background:
Excess bodyweight is a major public health concern. However, few worldwide comparative analyses of long-term trends of body-mass index (BMI) have been done, and none have used recent national health examination surveys. We estimated worldwide trends in population mean BMI.
Methods:
We estimated trends and their uncertainties of mean BMI for adults 20 years and older in 199 countries and territories. We obtained data from published and unpublished health examination surveys and epidemiological studies (960 country-years and 9·1 million participants). For each sex, we used a Bayesian hierarchical model to estimate mean BMI by age, country, and year, accounting for whether a study was nationally representative.
Findings:
Between 1980 and 2008, mean BMI worldwide increased by 0·4 kg/m(2) per decade (95% uncertainty interval 0·2-0·6, posterior probability of being a true increase >0·999) for men and 0·5 kg/m(2) per decade (0·3-0·7, posterior probability >0·999) for women. National BMI change for women ranged from non-significant decreases in 19 countries to increases of more than 2·0 kg/m(2) per decade (posterior probabilities >0·99) in nine countries in Oceania. Male BMI increased in all but eight countries, by more than 2 kg/m(2) per decade in Nauru and Cook Islands (posterior probabilities >0·999). Male and female BMIs in 2008 were highest in some Oceania countries, reaching 33·9 kg/m(2) (32·8-35·0) for men and 35·0 kg/m(2) (33·6-36·3) for women in Nauru. Female BMI was lowest in Bangladesh (20·5 kg/m(2), 19·8-21·3) and male BMI in Democratic Republic of the Congo 19·9 kg/m(2) (18·2-21·5), with BMI less than 21·5 kg/m(2) for both sexes in a few countries in sub-Saharan Africa, and east, south, and southeast Asia. The USA had the highest BMI of high-income countries. In 2008, an estimated 1·46 billion adults (1·41-1·51 billion) worldwide had BMI of 25 kg/m(2) or greater, of these 205 million men (193-217 million) and 297 million women (280-315 million) were obese.
Interpretation:
Globally, mean BMI has increased since 1980. The trends since 1980, and mean population BMI in 2008, varied substantially between nations. Interventions and policies that can curb or reverse the increase, and mitigate the health effects of high BMI by targeting its metabolic mediators, are needed in most countries.
Funding:
Bill & Melinda Gates Foundation and WHO.
Lifestyle-based interventions, which typically promote various behavior modification strategies, can serve as a setting for evaluating specific behaviors and strategies thought to promote or hinder weight loss. The aim of our study was to test the associations of self-monitoring (ie, self-weighing and food journal completion) and eating-related (ie, dietary intake, diet-related weight-control strategies, and meal patterns) behaviors with weight loss in a sample of postmenopausal overweight-to-obese women enrolled in a 12-month dietary weight loss intervention. Changes in body weight and adoption of self-monitoring and eating-related behaviors were assessed in 123 participants. Generalized linear models tested associations of these behaviors with 12-month weight change after adjusting for potential confounders. Mean percent weight loss was 10.7%. In the final model, completing more food journals was associated with a greater percent weight loss (interquartile range 3.7% greater weight loss; P<0.0001), whereas skipping meals (4.3% lower weight loss; P<0.05) and eating out for lunch (at least once a week, 2.5% lower weight loss; P<0.01) were associated with a lower amount of weight loss. These findings suggest that a greater focus on dietary self-monitoring, home-prepared meals, and consuming meals at regular intervals may improve 12-month weight loss among postmenopausal women enrolled in a dietary weight loss intervention.
The effects of breakfast consumption on energy intake and the responses to foods consumed later in the day remain unclear. Twelve men of healthy body weight who reported regularly consuming breakfast (mean ± SD age 23.4 ± 7.3 y; BMI 23.5 ± 1.7 kg/m(2)) completed 2 trials using a randomized crossover design. Participants were provided with a 1050-kJ liquid preload 150 min after consuming a standardized breakfast (B) (10% daily energy requirement and 14, 14, and 72% energy from protein, fat, and carbohydrate, respectively), or no breakfast (NB). Blood glucose and serum insulin responses to the preload (area under the curve) were higher in the NB condition (P < 0.05). Plasma FFA responses to the preload were higher in the NB condition (P < 0.01). Plasma glucagon-like peptide 1 (P < 0.01) and plasma peptide Y (P < 0.05) responses were higher after the preload in the B condition. Desire to eat, fullness, and hunger ratings collected immediately prior to consuming the preload were all different from the fasting values in the NB condition (P < 0.05). Thus, immediately prior to consuming the preload, the fullness rating was lower and hunger and desire to eat ratings were higher in the NB condition (P < 0.05). Energy intake at the lunchtime test meal was ~17% lower in the B condition (P < 0.01). In conclusion, missing breakfast causes metabolic and hormonal differences in the responses to foods consumed later in the morning as well as differences in subjective appetite and a compensatory increase in energy intake.
The aim was to investigate the association between breakfast consumption and long-term weight gain in an adult male population.
We evaluated prospective data on 20,064 U.S men, 46 to 81 years of age, who participated in the Health Professionals Follow-up Study. Data on body weight, dietary factors, and lifestyle variables were obtained by validated questionnaires. We examined weight gain during 10 years of follow-up.
Overall, 5,857 men had a weight gain of 5 kg or greater during 10 years of follow-up. Breakfast consumption was inversely associated with the risk of 5-kg weight gain after adjustment for age [hazard ratio (HR) = 0.77 (95% confidence interval [CI], 0.72 to 0.82)], and this association was independent of lifestyle and BMI at baseline [HR = 0.87 (95% CI, 0.82 to 0.93)]. Fiber and nutrient intakes partially explained the association between breakfast consumption and weight gain. The inverse association between breakfast consumption and weight gain was more pronounced in men with a baseline BMI of 25 kg/m(2) or lower [multivariate HR = 0.78 (95% CI, 0.70 to 0.87)] than in men who were overweight at baseline [HR = 0.92 (95% CI, 0.85 to 1.00)]. Furthermore, we observed that an increasing number of eating occasions in addition to three standard meals was associated with a higher risk of 5-kg weight gain [HR = 1.15 (95% CI, 1.06 to 1.25, for >or=2 vs. 0 additional eating occasions)].
These findings suggest that the consumption of breakfast may modestly contribute to the prevention of weight gain as compared with skipping breakfast in middle-aged and older men.