Plus, those who ate during this window were less likely to feel hungry than those who postponed their breakfast until after 10 a. Another reason to eat the most important meal of the day: Skipping it has been linked to a higher BMI.

Women who ate a calorie snack at 10 a. burned more fat than those who ate the same snack at 11 p. Studies also show that a light snack could lead you to eat less at mealtimes and may help you up your intake of low-calorie, nutrient-dense foods like fruits and vegetables.

Lunch break. The ringing phone, email notifications, and looming deadlines can make it tempting to postpone lunch, but waiting until late afternoon could cause you to overeat or make less healthy choices.

Research supports the idea of eating an earlier lunch. Late eaters—who grabbed lunch at p. Interestingly, despite eating a similar number of calories and micronutrients, dieters who ate lunch after 3 p. lost less weight than dieters who dined earlier.

Sitting down to a late supper could lead to weight gain. Jun published a small study that showed eating at 6 p. Eating an earlier dinner—and skipping late night snacking while binge-watching your favorite shows —could also help you sleep better. When those who normally ate one-third of their calories between 6 p.

and midnight, stopped eating between dinner and breakfast the next morning, their weight decreased, and their time in dreamland increased. A meal that is high in fiber and low in saturated fat can help you fall asleep faster.

Understanding the science behind meal timing—and adjusting when you eat breakfast, lunch, and dinner—could have a big impact on your health.

At optimum performance, they initiate wake and sleep cycles , and also signal feeding , and fasting bodily states. It is imperative that eating and sleeping behaviors align with circadian rhythms. When these rhythms are consistently disrupted, it can lead to an increased risk of obesity, type 2 diabetes, and cardiovascular diseases.

Mild dyssynchronous behavioral patterns such as variability in mealtimes and sleep patterns throughout the week are common, and are sometimes called social and eating jetlag. What does this mean for your mealtimes? Each of us requires a given amount of energy in calories each day.

This energy is harvested from the carbs, proteins, and fats that we consume. When we fail to eat adequately throughout the day for example, only one or two meals , it can be challenging to meet our energy and nutritional needs.

Regular meal timing also helps to promote regular digestive patterns. I recommend consuming something within two hours of waking up regardless of feeling hungry or not.

Sometimes we fail to recognize hunger early in the mornings because the body ceases hunger cues overnight during its powered-down state. However, I strongly encourage you to try having something small. This meal breaks the overnight fast and provides your body with fuel and nourishment to start and power throughout the day.

Meals should include a protein -rich food, high-fiber starches, vegetables, fruits, and fat. It is important to acknowledge and respond to your hunger cues regardless of a meal schedule.

There are various approaches to eating, and having a meal plan that makes you feel your best may not exactly suit someone else and vice versa. The sample schedule below may be a good place to start to see what works for you.

Break your fast. This window is the most recommended time to have breakfast. Think of a balanced breakfast as one that includes lean protein like eggs , lean pork sausage, tofu, Greek yogurt, nut butter, or plant seeds hemp, chia ; low-sugar fruit like berries , apples, citrus, or peaches; and , a complex carb like granola, whole wheat toast, or oats.

Snack it up. Given breakfast has now been a few hours ago and lunch still feels light years away, I recommend having something light but with flavors and nutrients that are complimentary of one another, like an apple with peanut butter, a handful of nuts with some cheese, or whole grain crackers with deli meat.

The high-fiber, high-protein combination is bound to curb hunger and cravings.

All-nighters in the library. A diet of coffee and gummy bears. Sound familiar? The foods you choose to eat have a definite impact on both your energy level and academic performance.

Poor eating habits can leave you feeling drained and struggling to remember what you spent hours learning. After a 12 or 14 hour fast, your body needs food in order to function at its best. Short on time? Try one of these 5-minute meal ideas, choosing whole grains whenever possible:.

Students who eat at regular intervals avoid energy slumps and the extreme hunger that can lead to binge eating. If your meals are more than four hours apart, have a snack. Stock the fridge, freezer and cupboards ahead of time with nutritious, easily-prepared foods: whole grain bread, cereals and pasta, pasta sauce, lentils, bean and vegetable soups, tuna, eggs, pre-cooked sliced meats or chicken, frozen fish fillets, ready-made salads, frozen veggies and fruit, fresh fruit, nuts, yogurt, cheese, and milk.

Although a handful of gummy bears may satisfy you for a few minutes, a quick sugar fix provides little brain fuel and is likely to leave you feeling more sluggish.

Research supports eating an earlier lunch. Those who eat lunch around are found to have decreased glucose tolerance, which can lead to decreased memory function and impaired cognition, compared to those who have lunch at pm.

Snack again. As with your morning snack, a high-fiber, high-protein combo is most effective for curbing hunger. Research supports having dinner at pm opposed to 10 pm increases usage of calories at rest. Eating an earlier dinner and skipping late night 10 pm and after meal can also help you sleep better.

A dinner that is high in fiber vegetables and c omplex carbs and low in saturated fat can help you fall asleep faster and increase your time in dreamland. If following the above schedule is incompatible with your schedule, at best try to consume a substantive meal every four hours, containing complex carbs like rice, potatoes, or grains; lean protein like eggs, chicken, beef, pork, tofu; and a vegetable, with water.

Be sure to keep pocket snacks containing protein on hand like protein bars, fruit snacks, and cheese sticks for durable energy between meals. Understanding the science behind meal timing could have a huge impact on your health, both physically and mentally.

It could be as simple as adjusting when you consume breakfast, lunch, dinner, and snacks along with their nutrient content. In summary:. Whatever you do, avoid skipping meals.

Your body is counting on you. Timing is everything: Why eating on a regular schedule supports overall well-being By Rayven Nairn, MS, RDN, LDN December 9, In studies where food intake is not fully controlled, the lack of influence of late eating on energy intake remains uncertain as most studies relied on self-reported dietary assessment tools without consideration of misreporting of energy intake which can result in attenuated or misleading associations Accounting for misreporting of energy intake may be particularly relevant in this context as underreporting is associated with obesity and is more likely to occur with foods of low nutritional value that may be perceived as socially undesirable 28 and that are associated with evening preferences 29 , Moreover, late eaters have been characterized as being more prone to eating when stressed, overeating at night and eating while watching television Disinhibition, which refers to an overconsumption of food triggered by different cues 31 , habitual and emotional susceptibility to disinhibition, and binge eating severity have also been associated with a higher proportion of TEI consumed as evening snacks Eating behaviour traits such as disinhibition, emotional eating and binge eating have been associated with higher energy intake, weight gain and obesity 33 — Although the behavioural characterization of late eaters in the literature is scarce, these results support the hypothesis that late eating may also impact body weight through energy intake.

To improve obesity treatment and prevention, there is a need to better understand how late eating impacts body weight.

Importantly, more studies accounting for systematic bias associated with dietary assessment tools or using objective measurement of dietary intake are needed to shed light on the possible association between late eating and energy intake.

Expanding the behavioural characterization of late eaters is also important as it could help develop targeted interventions for these individuals.

To our knowledge, only two studies have assessed eating behaviour traits associated with late eating 13 , Based on results from these two previous studies showing that late eating is associated with eating in response to negative emotions 13 , 32 , it is possible that late eaters are characterized by higher levels of psychosocial factors such as stress, anxiety and depressive symptoms, but this remains to be assessed.

The first objective of this study was to assess the associations between a late distribution of food intake i. The second objective was to examine the associations between late eating, eating behaviour traits and psychosocial factors i.

We hypothesised that late eating is associated with TEI and BMI and that TEI mediates the association between late eating and BMI. We also hypothesised that late eating is associated with overeating-related eating behaviour traits and that these traits mediate the association between late eating and TEI.

This cross-sectional study included baseline data from individuals with overweight or obesity from the Weight Loss Intervention Studies WeLIS Cohort, which includes four previous weight loss studies with similar designs conducted at Université Laval 41 — These studies aimed to assess the effect of various supplements i.

Each study was approved by the Research Ethics Board of Université Laval and written informed consent was obtained from each participant before the study. Anthropometric measurements were performed according to standardised procedures recommended at the Airlie Conference Body weight was measured to the nearest 0.

Dietary intakes were assessed with a three-day food record completed on two weekdays and one weekend day at baseline Participants received instructions on how to complete the food record and measure quantity of food consumed.

The research dietitian reviewed the completed food record with the participant to ensure that all information was clear and complete.

Food records were analyzed using the Nutrific software 47 linked to the Canadian Nutrient File version or , depending on the studies 48 , The distribution of food intake was assessed by calculating the percentage of TEI from six intervals throughout the day.

Period 1 corresponded to the first moment of food consumption recorded until , period 2 was from to , period 3 was from to , period 4 was from to , period 5 was from to and period 6 was from until the time of the last food consumption recorded.

The percentage of TEI from each period was calculated as the sum of the three-day energy intake from each period divided by the sum of the three-day TEI, multiplied by These periods were based on hours delimiting periods in previous American and Canadian studies 6 , 17 , 18 , 32 and adapted to the usual Canadian meal pattern i.

They were also designed to capture late eating and main peaks of intake i. Further details about the rationale behind the definition of time periods established in this study to assess the distribution of food intake have been previously published To obtain the percentage of TEI from morning, afternoon and evening, the periods were combined as follows: morning periods 1 and 2 , afternoon periods 3 and 4 and evening periods 5 and 6.

In the present study, we used the percentage of TEI consumed after i. A higher percentage of TEI consumed during the evening reflects a later distribution of food intake. Eating behaviour traits were assessed with the Three-Factor Eating Questionnaire TFEQ 31 , 54 and the Binge Eating Scale BES The TFEQ is a item questionnaire that measures three main dimensions of eating behaviour traits, namely cognitive restraint, disinhibition and susceptibility to hunger, with higher scores reflecting higher levels of these eating behaviours.

Cognitive restraint reflects the tendency to restrain food intake to control or lose body weight. It is assessed with 21 items and can be separated into specific types, namely rigid and flexible restraint, each assessed with 7 items Disinhibition is based on 16 items and reflects an overconsumption of food triggered by different cues representing its three subscales, namely habitual 5 items , emotional 3 items and situational 5 items susceptibility to disinhibition Susceptibility to hunger 14 items represents a susceptibility to experience feelings of hunger triggered by internal internal locus of hunger, 6 items or external external locus of hunger, 6 items cues Thirty-six items are in a true or false format coded as 0 or 1 and 15 items are based on a 4 or 6-point scale coded as 0 or 1.

The Binge Eating Scale assesses binge eating severity with 16 items describing the behavioural manifestations of binge eating and the feelings and cognitions surrounding binge eating episodes Items are on a scale of 0 to 2 or 0 to 3, providing a total score of 0 to 46, with higher scores denoting higher binge eating severity.

Psychosocial factors, namely stress, anxiety and depressive symptoms were assessed with questionnaires. This questionnaire comprises 10 items assessed on a 5-point scale coded as 0 to 4, providing a total score ranging from 0 to 40 The anxiety trait was assessed with 20 items of the State and Trait Anxiety Inventory STAI These items are measured on a 4-point scale, ranging from 1 to 4, providing a total score for the trait section ranging between 20 and Depressive symptoms were assessed with the Beck Depression Inventory BDI The questionnaire comprises 21 items assessed on a 4 to 6-point scale, scored from 0 to 3, which provide a total score for the questionnaire ranging between 0 and Higher scores on these questionnaires reflect higher levels of stress, anxiety or depressive symptoms 55 , 58 , 59 , Information on sex and age were collected at screening by the research staff.

Sleep duration and habitual bedtime over the last month were self-reported with two questions based on the Pittsburgh Sleep Quality Index Misreporting of energy intake was assessed by the method of Huang et al.

Resting metabolic rate was measured in a fasted state using indirect calorimetry in each study, as detailed elsewhere Since participants had to be inactive to low active to be included in each study, RMR was multiplied by a PAL coefficient of 1.

A PAL coefficient of 1. Assuming a standard PAL for each participant in the assessment of misreporting of energy intake has been previously done The ±1 standard deviation SD for confidence limits was established by using a within-individual coefficient of variation CV of To account for skewness of TEI, the ±1 SD confidence intervals were exponentiated using a multiplicative factor of 1 For participants with an objective measure of RMR, the resulting confidence interval was 0.

Individuals with values corresponding to or within the confidence interval were considered plausible reporters. Based on these values, two indicator variables were created to represent underreporting yes, 1; no, 0 and overreporting yes, 1; no, 0. Because misreporting is based on a deviation from an exact correspondence between rEI and TEE 27 , overreporting may also represent overconsumption in some individuals.

Consequently, the main analyses were only adjusted for underreporting, but overreporting was further considered in supplemental analyses. Adjustment, rather than exclusion of under- and overreporters was used as it has been suggested as a more appropriate way to address misreporting since it avoids selection bias and reduction in statistical power Ethnicity was also assessed at screening, but was not used as a covariate since there was low diversity in this sample.

Statistical analyses were performed using SAS version 9. Differences in these variables between studies were assessed with general linear models and Chi-square tests. The associations between the percentage of TEI consumed in the evening after and after and BMI, TEI, eating behaviour traits or psychosocial factors were assessed with Pearson correlations.

The main analyses were adjusted for age, sex men, 0; women, 1 , underreporting of energy intake, sleep duration and bedtime. Due to sex differences in eating behaviour traits 34 , 35 , linear regressions were used to investigate sex interactions in these associations.

Mediation analyses were conducted to assess if TEI mediates the potential associations between the percentage of TEI after or after and BMI. Mediation analyses were also performed to determine if the association between late eating and TEI is mediated by some eating behaviour traits that confer a susceptibility to overeating and showed a significant and positive association with late eating in correlation analyses.

These analyses were performed separately among men and women when a sex interaction was previously observed in regression analyses.

Mediation analyses were performed with model 4 of the Process macro for SAS, version 3. Process is an ordinary least square regression path analysis modelling tool that assesses the mediating or indirect effect through which an independent variable influences a dependent variable using percentile bootstrap confidence intervals The current study used 5, bootstrap samples.

In the mediation model, the association between the independent variable and the mediator is represented by path a , and the association between the mediator and the dependent variable, adjusted for the independent variable, is represented by path b. Mediation analyses were adjusted for the same covariates as correlations.

According to Hayes, a mediation effect could occur despite no evidence that the association between the independent and dependent variables is different from zero since the indirect effect is not determined nor constrained by the size of the total effect In secondary analyses, correlations and mediation models were adjusted for 1 age, sex and underreporting i.

Adjustment for the different studies was performed by creating three indicator variables for Major et al. The Sanchez et al. For the associations between late eating and binge eating severity, perceived stress and anxiety, only one indicator variable for Sanchez et al.

This study included women and men, with a mean age of Participants consumed Of this value, 9. Except for TEI, there were no differences in these baseline characteristics nor distribution of food intake between men and women.

However, as expected, there were several sex differences in eating behaviour traits, with women presenting higher levels of cognitive restraint 8. Women also reported higher levels of perceived stress Differences in participant characteristics, distribution of food intake, eating behaviour traits and psychosocial factors between studies included in this cohort are presented in Supplementary Table S1.

Note that differences between studies are mainly attributed to sex. No sex interaction was observed for these correlations data not shown. Similar results were observed for correlations that did not consider sleep duration and bedtime or that were further adjusted for overreporting of energy intake or the different studies Supplementary Table S2.

Similar results were observed after adjustment for the different sets of covariates Supplementary Table S3. The model adjusted for age, sex and underreporting of energy intake showed a significant mediating effect of TEI in the association between the percentage of TEI after and BMI, but the effect was similar to the original model.

Figure 1. Mediation of TEI in the association between the percentage of TEI after A or after B and BMI. Mediation analyses were conducted using the Process Macro v.

Models were adjusted for age continuous , sex men, 0; women, 1 , underreporting of energy intake yes, 1; no, 0 , sleep duration continuous and bedtime continuous. A sex by distribution of food intake interaction indicated different patterns of association in men and women for some eating behaviour traits and depressive symptoms.

Depressive symptoms were not associated with the percentage of TEI after neither in men nor in women. Again, these results remained similar after adjustment for the different sets of covariates Supplementary Tables S2, S4. Table 2.

Associations between the percentage of TEI after or after , eating behaviour traits and psychosocial factors a. Table 3. Associations between the percentage of TEI after or after and eating behaviour traits or depressive symptoms, respectively, in men and women a.

These results remained similar after adjustment for the different sets of covariates Supplementary Table S5. Figure 2. Models were adjusted for age continuous , underreporting of energy intake yes, 1; no, 0 , sleep duration continuous and bedtime continuous.

C,D are further adjusted for sex men, 0; women, 1. The timing of food intake has been identified as a risk factor for obesity. However, whether a late distribution of food intake impacts body weight through increased energy intake remains controversial and the behavioural characterization of late eaters needs to be further investigated.

This study first examined the associations between a late distribution of food intake and TEI, BMI and eating and psychosocial traits, while considering underreporting of energy intake. This study also aimed to assess whether TEI and eating behaviour traits mediate the association between late eating and BMI or TEI, respectively.

The results showed that a higher percentage of TEI during the evening was positively associated with TEI and that TEI mediated the association between the percentage of TEI after and BMI. The results also showed that late eating was associated with higher levels of disinhibition, susceptibility to hunger, stress and anxiety, and that disinhibition in women and susceptibility to hunger in men and women combined mediated the association between late eating and TEI.

Although cross-sectional, this study suggests that late eating could influence obesity through increased energy intake and that suboptimal eating behaviour traits could contribute to explaining the susceptibility to overeating among late eaters.

The association between the percentage of TEI in the evening and TEI was small, but consistent with previous observational studies 17 — Moreover, although late eating i. As indicated previously, an indirect effect can be different from zero even if the total effect is not This is explained by the fact that the size of the indirect effect is not constrained nor determined by the size of the total effect Through energy intake, the mediation models showed that each percent increase in TEI after resulted in 0.

For an individual 1. Given that the average increase in body weight among Canadian adults is 0. Several factors may explain why a late distribution of food intake may lead to higher energy intake. Ghrelin, hunger, appetite for specific foods i. This potentially facilitates a positive energy balance towards the end of the day.

These results were corroborated in an experimental study comparing appetite and food reward in response to a test meal during morning or late afternoon Appetite, liking and wanting for high-fat foods were higher and post-meal fullness was lower in the late meal condition The distribution of food intake may also influence appetite, as late eating resulted in higher daily levels of ghrelin and hunger and lower levels of fullness during weight loss Results of this latter study were recently corroborated in two cross-over randomised controlled trials in which all foods were provided to participants during weight loss or weight stable conditions 25 , These studies reported higher daily levels of hunger, prospective food consumption and desire to eat in the late eating condition 25 , Homeostatic and hedonic mechanisms may thus be implicated in the effect of late eating on TEI.

The possible effect of late eating on energy intake is also supported by positive, small to moderate associations between late eating and eating behaviour traits associated with overeating, namely disinhibition and susceptibility to hunger.

Moreover, these eating behaviours mediated the associations between late eating and TEI in women or in the whole group, respectively. These results are in line with previous studies showing that late eating was associated with overeating at night and emotional eating 13 and that evening snacking was positively associated with disinhibition More broadly, these results are also in line with studies on chronotype showing that evening type individuals, who also present a delayed food pattern 78 , 79 , are more likely to present higher levels of disinhibition, susceptibility to hunger and binge eating and lower levels of cognitive restraint 80 , While cross-sectional, these results collectively suggest that late eating could lead to overconsumption through suboptimal eating behaviour traits.

Disinhibition behaviours and overconsumption triggered by susceptibility to hunger may be more likely to occur during the evening as a result of homeostatic and hedonic mechanisms potentially facilitating overeating during the evening presented above.

Overeating associated with these eating behaviours may also be more likely to occur during the evening as a result of lower self-regulation capacity and increased tiredness 82 , eating because others are eating 83 , 84 , eating in front of television 83 , expecting eating to be more rewarding 83 , alcohol consumption 83 , 85 , and more opportunities to eat alone 83 or when at home compared to at work or at school.

It may also be a consequence of reduced energy intake during the day. Tani et al. showed that a lower proportion of TEI in the morning and in the afternoon were associated with higher energy intake during the evening, and a higher proportion of TEI during the evening was associated with higher TEI A reduced energy intake earlier in the day may also be a consequence of overeating during the evening.

Indeed, late eaters showed reduced morning appetite 13 and a Mendelian randomisation study showed that evening chronotype was causally associated with breakfast skipping, the latter also being causally associated with obesity Sex differences were observed in the associations between late eating and eating behaviour traits.

Women with disinhibition seem more susceptible to overeating after , while both men and women presenting higher levels of susceptibility to hunger, showed a higher percentage of TEI after This may be related to gender differences in social norms regarding food intake and body weight, as eating light meals are perceived as more feminine and heavy meals as more masculine Eating smaller meals during the day may promote overeating in women with disinhibition during the evening, when at home, as opposed to men who may not perceive such social pressure to restrain eating during the day.

Sex differences in chronotype may also be involved, as men usually present a later chronotype The positive associations between the proportion of TEI consumed after and psychosocial factors such as stress and anxiety are in line with a previous study showing that late eaters were more likely to eat when stressed More broadly, this is also in line with studies indicating that individuals with evening chronotype were more likely to experience negative psychological symptoms including anxiety 88 , emotional overeating and stress-related eating 79 , 89 , Because affective states and cognitive functioning worsen later in the day, resulting in a decrease in self-regulation capacity 82 , it may be hypothesised that individuals with higher levels of stress and anxiety are more susceptible to overeating during the evening or at night.

This hypothesis is supported by a study showing a positive association between psychological stress and self-reported overeating at dinner in workers More broadly, this is also in line with the literature showing a positive association between emotional overeating and evening snacking 32 and that evening and night eating are used to regulate negative emotions among individuals with night eating syndrome Participants of this latter study also reported that evening and night eating resulted in calmness Lastly, a positive association between stress and hunger was found to be predominant during late afternoon and evening 93 , which may also explain the increased susceptibility to overeating during the evening in individuals with stress and anxiety.

This study has several strengths and limitations. One of the main strengths is the use of a three-day food record with the consideration of underreporting of energy intake, and overreporting in supplemental analyses, to mitigate the effect of systematic bias in self-reported dietary assessment

Thus, scheduling mealtimes too closely to when your body releases the hormone, especially late in the evening, is a risk factor for chronic disease 20 , 26 , Each of us has a unique genetic profile and individual circumstances that dictate our daily schedule and help determine the best times to eat.

However, some research shows that eating a majority of daily calories earlier in the day may be ideal. A high intensity workout or an intense cardio session may require more precise meal timing.

On the other hand, a leisurely activity like walking lends greater flexibility. For pre-workout meals , eating an hour or two before you exercise helps fuel your muscles.

Just remember to give your meal enough time to begin digesting before you start any high intensity activities 41 , For post-workout meals , eating within 2 hours of finishing an activity may help replenish your energy stores and repair any muscle protein damage that occurred during the exercise Still, scientists have a lot to learn when it comes to exercise and mealtimes.

For example, some recent research suggests that eating before a workout rather than afterward may benefit blood sugar control Other studies have found that some people may perform better during aerobic exercises like running while still in an early-morning state of fasting Research on this topic is still emerging and sometimes contradictory, and it may depend on personal factors like individual health and the type of workout.

Thus, more studies are needed Though the best mealtimes will ultimately vary from person to person, there are some general suggestions for timing meals. Keep these three rules of thumb in mind when planning your mealtimes 26 , 46 :. The best times of day to eat will vary from person to person — and maybe even from day to day.

Consider eating the bulk of your calories earlier in the day, and try to avoid eating within a few hours of bedtime. Eating a majority of your calories earlier in the day and limiting how much you eat later in the evening or through the overnight hours may help your body digest your food more efficiently.

It may also reduce your risk of certain risk factors for metabolic conditions like diabetes and obesity. However, there is no magic bullet when it comes to mealtimes. The right eating schedule for you may depend on many factors, including your daily routine, health conditions, and genetics.

Nevertheless, by keeping the fundamentals of mealtimes in mind while allowing yourself flexibility, you can feel confident about your meal schedule — no matter what obstacles the day throws your way. Try this today : Did you know mealtimes can be especially important for people managing conditions like gastroesophageal reflux disease GERD and diabetes?

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Let's look deeper:. A Quiz for Teens Are You a Workaholic? How Well Do You Sleep? Health Conditions Discover Plan Connect. Nutrition Evidence Based When Should You Eat? The Best Times for Meals, Explained. Medically reviewed by Kim Chin, RD , Nutrition — By Cecilia Snyder, MS, RD on August 17, Why mealtimes matter.

The best times to eat. How to time meals for optimal workouts. Choosing your meal times. The bottom line. The distribution of food intake was assessed by calculating the percentage of TEI from six intervals throughout the day. Period 1 corresponded to the first moment of food consumption recorded until , period 2 was from to , period 3 was from to , period 4 was from to , period 5 was from to and period 6 was from until the time of the last food consumption recorded.

The percentage of TEI from each period was calculated as the sum of the three-day energy intake from each period divided by the sum of the three-day TEI, multiplied by These periods were based on hours delimiting periods in previous American and Canadian studies 6 , 17 , 18 , 32 and adapted to the usual Canadian meal pattern i.

They were also designed to capture late eating and main peaks of intake i. Further details about the rationale behind the definition of time periods established in this study to assess the distribution of food intake have been previously published To obtain the percentage of TEI from morning, afternoon and evening, the periods were combined as follows: morning periods 1 and 2 , afternoon periods 3 and 4 and evening periods 5 and 6.

In the present study, we used the percentage of TEI consumed after i. A higher percentage of TEI consumed during the evening reflects a later distribution of food intake. Eating behaviour traits were assessed with the Three-Factor Eating Questionnaire TFEQ 31 , 54 and the Binge Eating Scale BES The TFEQ is a item questionnaire that measures three main dimensions of eating behaviour traits, namely cognitive restraint, disinhibition and susceptibility to hunger, with higher scores reflecting higher levels of these eating behaviours.

Cognitive restraint reflects the tendency to restrain food intake to control or lose body weight. It is assessed with 21 items and can be separated into specific types, namely rigid and flexible restraint, each assessed with 7 items Disinhibition is based on 16 items and reflects an overconsumption of food triggered by different cues representing its three subscales, namely habitual 5 items , emotional 3 items and situational 5 items susceptibility to disinhibition Susceptibility to hunger 14 items represents a susceptibility to experience feelings of hunger triggered by internal internal locus of hunger, 6 items or external external locus of hunger, 6 items cues Thirty-six items are in a true or false format coded as 0 or 1 and 15 items are based on a 4 or 6-point scale coded as 0 or 1.

The Binge Eating Scale assesses binge eating severity with 16 items describing the behavioural manifestations of binge eating and the feelings and cognitions surrounding binge eating episodes Items are on a scale of 0 to 2 or 0 to 3, providing a total score of 0 to 46, with higher scores denoting higher binge eating severity.

Psychosocial factors, namely stress, anxiety and depressive symptoms were assessed with questionnaires. This questionnaire comprises 10 items assessed on a 5-point scale coded as 0 to 4, providing a total score ranging from 0 to 40 The anxiety trait was assessed with 20 items of the State and Trait Anxiety Inventory STAI These items are measured on a 4-point scale, ranging from 1 to 4, providing a total score for the trait section ranging between 20 and Depressive symptoms were assessed with the Beck Depression Inventory BDI The questionnaire comprises 21 items assessed on a 4 to 6-point scale, scored from 0 to 3, which provide a total score for the questionnaire ranging between 0 and Higher scores on these questionnaires reflect higher levels of stress, anxiety or depressive symptoms 55 , 58 , 59 , Information on sex and age were collected at screening by the research staff.

Sleep duration and habitual bedtime over the last month were self-reported with two questions based on the Pittsburgh Sleep Quality Index Misreporting of energy intake was assessed by the method of Huang et al. Resting metabolic rate was measured in a fasted state using indirect calorimetry in each study, as detailed elsewhere Since participants had to be inactive to low active to be included in each study, RMR was multiplied by a PAL coefficient of 1.

A PAL coefficient of 1. Assuming a standard PAL for each participant in the assessment of misreporting of energy intake has been previously done The ±1 standard deviation SD for confidence limits was established by using a within-individual coefficient of variation CV of To account for skewness of TEI, the ±1 SD confidence intervals were exponentiated using a multiplicative factor of 1 For participants with an objective measure of RMR, the resulting confidence interval was 0.

Individuals with values corresponding to or within the confidence interval were considered plausible reporters. Based on these values, two indicator variables were created to represent underreporting yes, 1; no, 0 and overreporting yes, 1; no, 0.

Because misreporting is based on a deviation from an exact correspondence between rEI and TEE 27 , overreporting may also represent overconsumption in some individuals. Consequently, the main analyses were only adjusted for underreporting, but overreporting was further considered in supplemental analyses.

Adjustment, rather than exclusion of under- and overreporters was used as it has been suggested as a more appropriate way to address misreporting since it avoids selection bias and reduction in statistical power Ethnicity was also assessed at screening, but was not used as a covariate since there was low diversity in this sample.

Statistical analyses were performed using SAS version 9. Differences in these variables between studies were assessed with general linear models and Chi-square tests. The associations between the percentage of TEI consumed in the evening after and after and BMI, TEI, eating behaviour traits or psychosocial factors were assessed with Pearson correlations.

The main analyses were adjusted for age, sex men, 0; women, 1 , underreporting of energy intake, sleep duration and bedtime.

Due to sex differences in eating behaviour traits 34 , 35 , linear regressions were used to investigate sex interactions in these associations. Mediation analyses were conducted to assess if TEI mediates the potential associations between the percentage of TEI after or after and BMI.

Mediation analyses were also performed to determine if the association between late eating and TEI is mediated by some eating behaviour traits that confer a susceptibility to overeating and showed a significant and positive association with late eating in correlation analyses.

These analyses were performed separately among men and women when a sex interaction was previously observed in regression analyses. Mediation analyses were performed with model 4 of the Process macro for SAS, version 3. Process is an ordinary least square regression path analysis modelling tool that assesses the mediating or indirect effect through which an independent variable influences a dependent variable using percentile bootstrap confidence intervals The current study used 5, bootstrap samples.

In the mediation model, the association between the independent variable and the mediator is represented by path a , and the association between the mediator and the dependent variable, adjusted for the independent variable, is represented by path b.

Mediation analyses were adjusted for the same covariates as correlations. According to Hayes, a mediation effect could occur despite no evidence that the association between the independent and dependent variables is different from zero since the indirect effect is not determined nor constrained by the size of the total effect In secondary analyses, correlations and mediation models were adjusted for 1 age, sex and underreporting i.

Adjustment for the different studies was performed by creating three indicator variables for Major et al. The Sanchez et al. For the associations between late eating and binge eating severity, perceived stress and anxiety, only one indicator variable for Sanchez et al.

This study included women and men, with a mean age of Participants consumed Of this value, 9. Except for TEI, there were no differences in these baseline characteristics nor distribution of food intake between men and women.

However, as expected, there were several sex differences in eating behaviour traits, with women presenting higher levels of cognitive restraint 8. Women also reported higher levels of perceived stress Differences in participant characteristics, distribution of food intake, eating behaviour traits and psychosocial factors between studies included in this cohort are presented in Supplementary Table S1.

Note that differences between studies are mainly attributed to sex. No sex interaction was observed for these correlations data not shown. Similar results were observed for correlations that did not consider sleep duration and bedtime or that were further adjusted for overreporting of energy intake or the different studies Supplementary Table S2.

Similar results were observed after adjustment for the different sets of covariates Supplementary Table S3. The model adjusted for age, sex and underreporting of energy intake showed a significant mediating effect of TEI in the association between the percentage of TEI after and BMI, but the effect was similar to the original model.

Figure 1. Mediation of TEI in the association between the percentage of TEI after A or after B and BMI. Mediation analyses were conducted using the Process Macro v. Models were adjusted for age continuous , sex men, 0; women, 1 , underreporting of energy intake yes, 1; no, 0 , sleep duration continuous and bedtime continuous.

A sex by distribution of food intake interaction indicated different patterns of association in men and women for some eating behaviour traits and depressive symptoms.

Depressive symptoms were not associated with the percentage of TEI after neither in men nor in women. Again, these results remained similar after adjustment for the different sets of covariates Supplementary Tables S2, S4.

Table 2. Associations between the percentage of TEI after or after , eating behaviour traits and psychosocial factors a. Table 3. Associations between the percentage of TEI after or after and eating behaviour traits or depressive symptoms, respectively, in men and women a.

These results remained similar after adjustment for the different sets of covariates Supplementary Table S5. Figure 2. Models were adjusted for age continuous , underreporting of energy intake yes, 1; no, 0 , sleep duration continuous and bedtime continuous.

C,D are further adjusted for sex men, 0; women, 1. The timing of food intake has been identified as a risk factor for obesity. However, whether a late distribution of food intake impacts body weight through increased energy intake remains controversial and the behavioural characterization of late eaters needs to be further investigated.

This study first examined the associations between a late distribution of food intake and TEI, BMI and eating and psychosocial traits, while considering underreporting of energy intake. This study also aimed to assess whether TEI and eating behaviour traits mediate the association between late eating and BMI or TEI, respectively.

The results showed that a higher percentage of TEI during the evening was positively associated with TEI and that TEI mediated the association between the percentage of TEI after and BMI.

The results also showed that late eating was associated with higher levels of disinhibition, susceptibility to hunger, stress and anxiety, and that disinhibition in women and susceptibility to hunger in men and women combined mediated the association between late eating and TEI.

Although cross-sectional, this study suggests that late eating could influence obesity through increased energy intake and that suboptimal eating behaviour traits could contribute to explaining the susceptibility to overeating among late eaters.

The association between the percentage of TEI in the evening and TEI was small, but consistent with previous observational studies 17 — Moreover, although late eating i. As indicated previously, an indirect effect can be different from zero even if the total effect is not This is explained by the fact that the size of the indirect effect is not constrained nor determined by the size of the total effect Through energy intake, the mediation models showed that each percent increase in TEI after resulted in 0.

For an individual 1. Given that the average increase in body weight among Canadian adults is 0. Several factors may explain why a late distribution of food intake may lead to higher energy intake. Ghrelin, hunger, appetite for specific foods i. This potentially facilitates a positive energy balance towards the end of the day.

These results were corroborated in an experimental study comparing appetite and food reward in response to a test meal during morning or late afternoon Appetite, liking and wanting for high-fat foods were higher and post-meal fullness was lower in the late meal condition The distribution of food intake may also influence appetite, as late eating resulted in higher daily levels of ghrelin and hunger and lower levels of fullness during weight loss Results of this latter study were recently corroborated in two cross-over randomised controlled trials in which all foods were provided to participants during weight loss or weight stable conditions 25 , These studies reported higher daily levels of hunger, prospective food consumption and desire to eat in the late eating condition 25 , Homeostatic and hedonic mechanisms may thus be implicated in the effect of late eating on TEI.

The possible effect of late eating on energy intake is also supported by positive, small to moderate associations between late eating and eating behaviour traits associated with overeating, namely disinhibition and susceptibility to hunger. Moreover, these eating behaviours mediated the associations between late eating and TEI in women or in the whole group, respectively.

These results are in line with previous studies showing that late eating was associated with overeating at night and emotional eating 13 and that evening snacking was positively associated with disinhibition More broadly, these results are also in line with studies on chronotype showing that evening type individuals, who also present a delayed food pattern 78 , 79 , are more likely to present higher levels of disinhibition, susceptibility to hunger and binge eating and lower levels of cognitive restraint 80 , While cross-sectional, these results collectively suggest that late eating could lead to overconsumption through suboptimal eating behaviour traits.

Disinhibition behaviours and overconsumption triggered by susceptibility to hunger may be more likely to occur during the evening as a result of homeostatic and hedonic mechanisms potentially facilitating overeating during the evening presented above.

Overeating associated with these eating behaviours may also be more likely to occur during the evening as a result of lower self-regulation capacity and increased tiredness 82 , eating because others are eating 83 , 84 , eating in front of television 83 , expecting eating to be more rewarding 83 , alcohol consumption 83 , 85 , and more opportunities to eat alone 83 or when at home compared to at work or at school.

It may also be a consequence of reduced energy intake during the day. Tani et al. showed that a lower proportion of TEI in the morning and in the afternoon were associated with higher energy intake during the evening, and a higher proportion of TEI during the evening was associated with higher TEI A reduced energy intake earlier in the day may also be a consequence of overeating during the evening.

Indeed, late eaters showed reduced morning appetite 13 and a Mendelian randomisation study showed that evening chronotype was causally associated with breakfast skipping, the latter also being causally associated with obesity Sex differences were observed in the associations between late eating and eating behaviour traits.

Women with disinhibition seem more susceptible to overeating after , while both men and women presenting higher levels of susceptibility to hunger, showed a higher percentage of TEI after This may be related to gender differences in social norms regarding food intake and body weight, as eating light meals are perceived as more feminine and heavy meals as more masculine Eating smaller meals during the day may promote overeating in women with disinhibition during the evening, when at home, as opposed to men who may not perceive such social pressure to restrain eating during the day.

Sex differences in chronotype may also be involved, as men usually present a later chronotype The positive associations between the proportion of TEI consumed after and psychosocial factors such as stress and anxiety are in line with a previous study showing that late eaters were more likely to eat when stressed More broadly, this is also in line with studies indicating that individuals with evening chronotype were more likely to experience negative psychological symptoms including anxiety 88 , emotional overeating and stress-related eating 79 , 89 , Because affective states and cognitive functioning worsen later in the day, resulting in a decrease in self-regulation capacity 82 , it may be hypothesised that individuals with higher levels of stress and anxiety are more susceptible to overeating during the evening or at night.

This hypothesis is supported by a study showing a positive association between psychological stress and self-reported overeating at dinner in workers More broadly, this is also in line with the literature showing a positive association between emotional overeating and evening snacking 32 and that evening and night eating are used to regulate negative emotions among individuals with night eating syndrome Participants of this latter study also reported that evening and night eating resulted in calmness Lastly, a positive association between stress and hunger was found to be predominant during late afternoon and evening 93 , which may also explain the increased susceptibility to overeating during the evening in individuals with stress and anxiety.

This study has several strengths and limitations. One of the main strengths is the use of a three-day food record with the consideration of underreporting of energy intake, and overreporting in supplemental analyses, to mitigate the effect of systematic bias in self-reported dietary assessment As day-to-day variation was observed in the timing of food intake, combining several days of food intake is more likely to reflect a more habitual daily distribution of food intake than a single day 78 , The distribution of food intake was based on meal and snack times reported on the food record, which is more precise than using meals and snacks without considering hours.

However, this classification is limited by not being defined relative to endogenous circadian timing or sleep—wake cycle 3. Yet, the consideration of mean sleep duration and bedtime over the last month as covariates suggests that the associations observed are not simply reflecting a shifted sleep—wake cycle providing more opportunities to eat in the evening in individuals with later bedtime and shorter sleep duration.

It should be noted that these sleep parameters could have been more accurately assessed using objective measurements e. One main limitation is the cross-sectional design that precludes causation to be inferred.

Moreover, the relatively low sample size resulted in lower capacity to detect statistically significant results for some analyses. In addition, since the WeLIS cohort includes individuals living with overweight and obesity who are interested in losing weight, the results of this study may not be generalizable to other populations.

Replication of these results within larger longitudinal cohorts and with objective measurements of food intake are needed. In conclusion, this study suggests that late eating is positively associated with TEI, which may be related to higher BMI, in the long term.

This association is supported by positive associations between late eating and eating behaviour traits, which contributed to explaining the susceptibility to overeating among late eaters. These results suggest that the timing of food intake and eating behaviour traits are important determinants to consider in obesity treatment and prevention.

The datasets presented in this article are not readily available because it will be made available upon request pending approval from the authors as well as the funding agency. Requests to access the datasets should be directed to vicky. drapeau fse. The studies involving human participants were reviewed and approved by Research Ethics Board of Université Laval.

The participants provided their written informed consent to participate in their respective study. VD and RJ designed research. RJ collected data related to the timing of food intake, analyzed data, and wrote the first draught of the manuscript.

VD had primary responsibility for the final content. All authors contributed to the article and approved the submitted version. RJ is the recipient of PhD scholarships from the Fonds de recherche du Québec—Santé FRQS and Canadian Institutes of Health Research CIHR, MFE AT is the holder of the Canada Research Chair in Environment and Energy Balance.

MEM holds a Canada Research Chair Tier 1 in Physical Activity and Juvenile Obesity The funding agencies were not involved in designing and conducting the study, analyzing and interpreting the data or preparing and reviewing the manuscript before submission.

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers.

Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher. TEI, total energy intake; Percent TEI, percentage of total energy intake; TFEQ, Three-Factor Eating Questionnaire; rEI, self-reported energy intake; TEE, total energy expenditure; RMR, resting metabolic rate; PAL, physical activity level.

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