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Meal distribution across the day and itsrelationship with body compositionMurilo Dattilo a , Cibele Aparecida Crispim a , Ioná ZalcmanZimberg a , Sérgio Tufik a & Marco Túlio de Mello aa Departamento de Psicobiologia , Universidade Federal de SãoPaulo , Sao Paulo, BrazilPublished online: 15 Jul 2010.

To cite this article: Murilo Dattilo , Cibele Aparecida Crispim , Ioná Zalcman Zimberg , SérgioTufik & Marco Túlio de Mello (2011) Meal distribution across the day and its relationship with bodycomposition, Biological Rhythm Research, 42:2, 119-129, DOI: 10.1080/09291011003729270

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Meal distribution across the day and its relationship with body

composition

Murilo Dattilo, Cibele Aparecida Crispim, Iona Zalcman Zimberg,Sergio Tufik and Marco Tulio de Mello*

Departamento de Psicobiologia, Universidade Federal de Sao Paulo, Sao Paulo, Brazil

(Received 13 January 2010; final version received 24 February 2010)

Evidence has suggested that meal distribution across the day may influence bodycomposition. This study aimed to evaluate the distribution of energy andmacronutrient intake in healthy men and women, and to correlate it with bodycomposition. Fifty-two healthy volunteers (24 men), aged 20–45 years old,participated in the study. Food intake was analyzed by a three-day food recordand anthropometric measurements included body mass, height, body mass index,body fat percentage, and waist circumference. Positive correlations were found inmen between night fat intake and body mass index, body fat percentage and waistcircumference and negative correlations were seen between morning energy andmacronutrient intake and the same anthropometric variables. These data suggestthat fat intake at night is associated with higher values in anthropometric variableswhile morning food intake can be associated with lower values in anthropometricvariables.

Keywords: meal distribution; body mass; waist circumference; obesity; body fat

Introduction

Factors which lead to an increase of body mass have been of interest for severalinvestigators (World Health Organization 2000; Bes-Rastrollo et al. 2006), as obesityis highly related to the development of type 2 diabetes mellitus (Turkoglu et al. 2003;Gregg et al. 2005) and cardiovascular diseases (Gregg et al. 2005). There is conciseevidence demonstrating that the type of diet consumed, coupled with an increase in asedentary lifestyle, are the main factors responsible for establishing a positive energybalance and consequent increase of body fat (Astrup 2001).

Although the question ‘‘what to eat?’’ has been extensively studied, little isknown about the best time to eat meals, how it should be distributed across the day,or even if these aspects are important (Holmback et al. 2003; Crispim et al. 2007). Itis well known that several physiological aspects present a circadian rhythm, like therate of gastric emptying, intestinal blood flow, renal and hepatic activity (Dunbaret al. 1989), hormonal responses to food intake (Astrup 2001; Holmback et al. 2003),insulin sensitivity and glucose tolerance (Van Cauter et al. 1991), lipid tolerance(Arasaradnam et al. 2002) and diet-induced thermogenesis (Romon et al. 1993), withlower efficiency being observed at night and increased efficiency in the morning.

*Corresponding author. Email: tmello@psicobio.epm.br

Biological Rhythm Research

Vol. 42, No. 2, April 2011, 119–129

ISSN 0929-1016 print/ISSN 1744-4179 online

� 2011 Taylor & Francis

DOI: 10.1080/09291011003729270

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Thus, the integration of such aspects in response to food intake may contribute tophysiological changes in digestion, absorption, and utilization of nutrients, that,associated with different values of diet-induced thermogenesis and levels of physicalactivity across the day (e.g. higher in the morning and lower at night), could becapable of influencing long-term body weight regulation.

Supporting this hypothesis, previous studies have suggested that the period of theday when meals are consumed may significantly influence body composition (Baeckeet al. 1983). In animals, food intake during the 12-h light phase is associated with asignificant weight gain in comparison with mice fed during the 12-h dark phase (Arbleet al. 2009). In humans, this hypothesis was cited by epidemiological investigations ofthe circadian distribution of energy intake, which have suggested that obeseindividuals consume a greater proportion of energy in the latter half of the daywhen compared with lean subjects, both in children (Maffeis et al. 2000) and adults(Bellisle et al. 1988; Fricker et al. 1990). Furthermore, studies involving night workershave also indicated that these individuals present a greater risk of developing obesity(Geliebter et al. 2000; Morikawa et al. 2007; Suwazono et al. 2008), and eating food atnight is a possible contributory factor (van Amelsvoort et al. 1999).

From another perspective, some previous data have indicated that theconsumption of meals in the morning, like breakfast meals, may have an importantrole in health promotion (Song et al. 2005; Huang et al. in press). As mentionedbefore, the morning period is associated with a higher metabolic and physiologicalefficiency, and is particularly satiating, contributing to reduce the total amountingested for the day (de Castro 2004). Moreover, some research has demonstratedthat consumption of meals in the morning contributes to body weight reduction,preventing weight gain and hence the development of obesity (Song et al. 2005; Kantet al. 2008; Huang et al. in press; Patro and Szajewska in press).

Taking that into consideration, the present study aimed to evaluate thedistribution of energy and macronutrient intake in healthy men and women, andto correlate it with body composition variables. With these analyses, we expect toobtain data that allows a better explanation of the relationship between eating ameal at different times of the day and body composition.

Methods

Subjects

The sample consisted of 24 men and 28 women, between 19 and 45 years old(27.2 + 5.9 and 28.8 + 6.6 years old, respectively). All individuals were sedentaryaccording to the Baecke et al. (1982) questionnaire and without health problems, likedyslipidemia, diabetes, cardiovascular disease, hypertension and sleep disturbance,according to medical evaluation, clinical and polysomnographic tests. Participation inthe study was voluntary after signing a written informed consent. Furthermore, allindividuals knew that they could interrupt their participation in the study at any givenmoment, without any cost. The present study was approved by the Committee ofEthics in Research of the Universidade Federal de Sao Paulo, under protocol #0592/07.

Food intake evaluation

The volunteers were instructed to provide as much detail as possible of the food andfluids consumed, including brand names and recipes for home-cooked foods. Portion

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sizes were estimated using common household measurements such as cups, glasses,bowls, teaspoons, and tablespoons in addition to individual food items/units. Thevolunteers discussed their reported food intake with a qualified nutritionist and theinformation was amended to include additional explanations and details, thusimproving the accuracy of the information obtained. Nutwin version 1.5 software(Universidade Federal de Sao Paulo, Brazil) was used for the quantitative analysis ofenergy and nutrient intake.

Body composition

Body mass was measured with a scale with 0.1 kg precision (Plenna1, PlennaEspecialidades Ltda, Brazil) and height with a stadiometer fixed to the wall with0.1 cm precision (Sanny1, American Medical do Brasil Ltda, Brazil). Body massdivided by the squared height was used to calculate the body mass index (BMI) inkg/m2.

For the evaluation of body composition, body densities were determinedaccording to the formulas proposed by Jackson and Pollock (1978) and Jacksonet al. (1980), for men and women, respectively. Skinfold fat was measured at thechest, axilla, triceps, subscapula, abdomen, supra-illac, and thigh using a Lange1

skinfold caliper (Beta Technology Incorporated, USA). Body fat percentage (%BF)was obtained using the formula proposed by Siri (1961). The measurements of waistcircumference (WC) were taken midway between the lowest rib and the iliac crestwith an inelastic measuring tape (Sanny1, American Medical do Brasil Ltda, Brazil).

Statistical analysis

Data were analyzed with Statistica 7.0 (StatSoft, Inc., Tulsa, OK, USA). All valueswere expressed as mean + standard deviation (SD). For gender comparisonsbetween food intake, Student’s t-tests for independent samples were used. Pearson’scorrelation coefficients were used to assess the association between food intakevariables (proportions of overall intake ingested during each period) andanthropometric measurements (BMI, %BF, WC). ANOVA with repeated measure-ments was used to compare the energy intake of meals and energy and macronutrientintake in accordance with morning (breakfast and mid-morning snack), afternoon(lunch and mid-afternoon snack) and night (dinner and supper) periods. Whensignificant differences were obtained, the tests were followed by Bonferroni’scorrections for multiple comparisons. Statistical tests when P � 0.05 were acceptedas significant.

Results

Table 1 presents the anthropometric characteristics of the subjects. The sample wascomposed of young adults and mean BMI and WC for both genders indicatesnormal ranges.

Although the values of energy intake were higher in men in relation to women(2697.6 + 870.6 kcal and 1865.5 + 502.1 kcal; P 5 0.01, respectively), nosignificant differences between genders in macronutrient intake (expressed per kgbody weight and also as a percentage of total intake) were identified (Table 2).

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Figure 1 depicts the energy distribution of the meals eaten during the course ofthe day in men and women. Differences were obtained for women [F (5,35) ¼ 9.71,P 5 0.01], and post-hoc analyses showed that lunch was significantly higher thanbreakfast (P ¼ 0.01), mid-morning snack (P 5 0.01), mid-afternoon snack(P 5 0.01), and supper (P ¼ 0.01), whereas dinner was higher than mid-morningsnack (P ¼ 0.07). For men, no differences were seen for any meal [F (5,20) ¼ 1.20,P ¼ 0.35].

Figure 2 shows data from the daily meals divided into three periods of the day(morning, afternoon and night) and gender, in accordance with energy (kcal),carbohydrate (g), protein (g), and fat (g) intake. Energy intake was higher in theafternoon and night than in the morning, for men [F (2,46) ¼ 12.6, P 5 0.01] andwomen [F (2,50) ¼ 12.19, P 5 0.01]. Carbohydrate intake at night was higher thanin the morning for men [F (2,46) ¼ 4.67, P ¼ 0.01] and afternoon intake was higherthan in the morning for women [F (2,50) ¼ 7.15, P 5 0.01]. Protein intake atafternoon and night was higher than in the morning, for men [F (2,46) ¼ 19.39,P 5 0.01] and women, whereas afternoon was higher than night for women [F(2,50) ¼ 18.16, P 5 0.01]. Fat intake in the afternoon and night was higher than inthe morning, for men [F (2,46) ¼ 16.11, P 5 0.01] and women [F (2,50) ¼ 7.43,P 5 0.01].

In Table 3, meal intakes are distributed into 3 periods – morning, afternoon andnight – and the respective correlations of each period with %BF, BMI and WC arepresented for both genders. Among men, significant negative correlations wereobserved for total energy and macronutrient intake in the morning and a positive

Table 1. Descriptive data of the subjects.

Variables Men (n ¼ 24) Women (n ¼ 28)

Age (yrs) 27.2 + 5.9 28.8 + 6.6Height (cm) 175.0 + 6.2 161.5 + 5.6Body mass (kg) 76.6 + 14.7 58.0 + 8.3BMI (kg/m2) 24.9 + 4.2 22.2 + 2.6Body fat (%) 19.4 + 7.7 22.0 + 5.1WC (cm) 84.9 + 11.9 71.8 + 6.6

BMI, Body Mass Index; WC, Waist circumference.

Table 2. Food intake data for men and women.

Nutritional composition of food intake Men (n ¼ 24) Women (n ¼ 28) P x

EI (kcal) 2697.6 + 870.6 1865.5 + 502.1 50.001Kcal (kcal/kg) 36.9 + 15.5 32.8 + 10.1 0.27Total fat intake (%EI) 31.5 + 5.9 30.7 + 5.2 0.60Total fat intake (g/kg) 1.2 + 0.5 1.1 + 0.5 0.44Total carbohydrate intake (%EI) 51.9 + 8.2 52.8 + 5.3 0.64Total carbohydrate intake (g/kg) 4.9 + 2.7 4.3 + 1.5 0.33Total protein intake (%EI) 16.6 + 3.9 16.6 + 5.4 0.95Total protein intake (g/kg) 1.5 + 0.6 1.3 + 0.4 0.15

EI, Energy intake. xComparison done by using Student’s t test.

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correlation was found between fat intake at night and %BF, BMI, and WC; forwomen, a single significant positive correlation was found in the afternoon for %BF.

For the correlations between energy intake in each period and overall intake,significant results were obtained only for the total sample (Figure 3). In summary,correlations with small magnitude were found in the morning. In the afternoon, thevalues indicated a negative correlation (r ¼ 70.29, P 5 0.05), whereas at night, thecorrelations were positive (r ¼ 0.34, P 5 0.05), suggesting that ingesting a highproportion of the daily intake in the afternoon was associated with lower overall

Figure 1. Comparison of the energy contents of the six daily meals in men and women.*Different from breakfast, mid-morning snack, mid-afternoon snack, and supper in men,P 5 0.01. #Different from mid-morning snack in women, P 5 0.01.

Figure 2. Nutritional composition of the different meals in men and women in accordancewith the period of day. *Different from morning, in men. #Different from morning, in women.¥Different from night, in women.

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intake and that ingesting a high proportion of daily intake in at night was associatedwith higher overall intake.

Discussion

Although studies developed with the same aim as ours are limited in the literature,we expected to obtain data to support the hypothesis that food intake at night might

Table 3. Correlation between food intake data and anthropometric variables in the morning,afternoon and night periods.

Men (n ¼ 24) Women (n ¼ 28)

%BF BMI WC %BF BMI WC

Kcal

Morning 70.57 70.60 70.60 70.20 70.11 70.03Afternoon 0.22 0.31 0.23 0.21 0.17 0.18Night 0.31 0.25 0.32 0.01 70.05 70.14Carbohydrate

Morning 70.59 70.61 70.61 70.09 0.02 0.02Afternoon 0.24 0.24 0.14 70.11 0.01 0.03Night 0.11 70.01 0.09 0.01 70.02 70.18Protein

Morning 70.40 70.42 70.43 70.23 70.11 70.04Afternoon 0.19 0.29 0.34 0.41 0.26 0.20Night 0.13 0.09 0.20 0.12 0.09 70.09Fat

Morning 70.44 70.49 70.47 70.28 0.10 70.09Afternoon 0.02 0.15 0.09 0.19 70.02 70.18Night 0.46 0.55 0.50 70.04 70.10 70.06

%BF, Body fat percentage; BMI, Body Mass Index; WC, Waist Circumference. Bold correlationcoefficients: P 5 0.05.

Figure 3. Correlation between energy intake in each period and overall intake. *P 5 0.05.

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contribute to increases in %BF, BMI, and WC. In fact, we observed a positivecorrelation between fat intake at night and these variables, an issue that highlightsseveral points related to health, but another important find of this study was thenegative correlation of total energy and all macronutrient intake in the morning andsuch anthropometric variables, similarly with previous data that emphasizes theimportance of food intake in this period, like breakfast.

Several physiological aspects are marked by a circadian rhythm, many of whichare associated with post-prandial metabolism. However, evidence that guides specificmodifications in food intake distribution across the day are very scarce (Waller et al.2004). According to the ‘‘lipogenic–lipolytic’’ theory of Armstrong (1980), daytimefood intake is associated with glucose metabolism and fat deposition, and nocturnal(sleep) fasting with fat metabolism. So, rhythmic alterations of post-prandialresponses at night, associated with metabolism peculiarities during sleep, indicatesthat the body is preparing to sleep, presenting a lower capacity to deal with food inthis period.

Our data suggest a possible interaction between fat intake and metabolicalterations that are observed at night, such as fat tolerance reduction, which is linkedto insulin resistance (Arasaradnam et al. 2002), and a reduced physical activity level,contributing together for fat deposition as adipose tissue. Fat metabolism showsdistinct features compared to glucose and amino acid metabolism, that is, unlikethese, increased fat intake is not accompanied by an increase in its oxidation,favoring lipogenesis and weight gain (Schutz et al. 1989). Moreover, carbohydrateintake at night may not be directly implicated with lipogenesis de novo (fat synthesisfrom non-lipid substrates), but it can contribute to weight gain and fat deposition byacting as ‘‘sparing’’ of fat oxidation (Schutz et al. 1989). In this way, excessive caloricintake during the evening hours is problematic (Russ et al. 1984) and avoiding high-density foods in this period, like high fat food, might aid in reducing overall intakeand may be useful in dietary interventions for overweight and obesity (de Castro2009).

Nowadays, this issue may be highlighted in front of the widespread use ofartificial lighting that has allowed people to remain active and eat late into the night(de Castro 2004), like night workers, for example. Individuals who work at night,that curiously present a higher prevalence of obesity (Waterhouse et al. 2003;Ishizaki et al. 2004), dyslipidemia (Lennernas et al. 1994), and type 2 diabetesmellitus (Gottlieb et al. 2005), are influenced by several factors, endogenously andexogenously. With regard to exogenous factors, food intake can be focused and it iswell described that night workers have an increased consumption of snacks andsmall, ‘‘convenience’’ meals during the shift itself (Lennernas et al. 1995), that areusually high in fat content. In fact, our study did not include night workers in thesample, but our data can be extrapolated, for instance, to this population as a toolfor nutritional strategies and interventions to reduce and prevent health problemslinked, partially, to food intake.

Recent studies have suggested that food intake during the morning period can beinvolved with weight gain prevention in adults (Cho et al. 2003; Song et al. 2005;Kant et al. 2008; Huang et al. in press) and youth (Alexander et al. 2009;Kontogianni et al. 2010; Patro and Szajewska in press). The fact that we found aninverse association between food intake in this period and BMI, %BF, and WC,corroborate directly with these findings. However, most of the studies utilized BMIas a tool for determination of nutritional status, while we observed these results for

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%BF and WC. Song et al. (2005) investigated the association between breakfastintake and BMI, using data from the National Health and Nutrition ExaminationSurvey (NHANES) 1999–2000, and observed that women who consumed breakfastshowed a significantly lower risk of presenting BMI 4 25 kg/m2 after adjustmentsfor age, race, smoking, energy intake, exercise and body mass control. In this sameway, Kant et al. (2008) evaluated data from NHANES 1999–2000, 2001–2002 and2003–2004 and observed that individuals who consumed breakfast had lower energydensity based on the 24-h food record, indicating that food intake during themorning may contribute to the reduction of total energy intake and contribute toweight maintenance and fat loss. Furthermore, women (but not men) who atebreakfast had a lower BMI compared with those who did not (27.9 + 0.2 kg/m2

versus 29.4 + 0.4 kg/m2, P ¼ 0.001).Because of strong evidence suggesting that breakfast consumption is a protection

factor against weight gain, both in adults and children, it is important to describe thepaper published by Alexander et al. (2009) that used magnetic resonance imaging asa tool for body composition evaluation. In this study, the authors observed thatbreakfast omission was associated with increased adiposity, specifically intra-abdominal adipose tissue in 93 overweight Latino youth (10–17 years old).Moreover, they postulated that interventions focused on increasing breakfastconsumption are warranted.

In accordance with the studies previously cited (Cho et al. 2003; Song et al. 2005;Kant et al. 2008; Alexander et al. 2009; Kontogianni et al. 2010; Huang et al. inpress; Patro and Szajewska in press), it is becoming more concrete that food intake inthe morning is a protection against weight gain. Contrary to taking a meal at night,food intake in the morning seems to contribute to lower energy storage as body fat,due to increased daytime activity (Segal et al. 1985). Moreover, according to Romonet al. (1993) food intake in the morning period (9:00 am) is associated with a greaterthermal effect than intake in the afternoon (5:00 pm) and night (1:00 am) periods;this difference leads to greater daily energy expenditure and favors the maintenanceof body mass. A study conducted by de Castro (2004) also indicates that mealdistribution during the course of the day may influence the energy value of the foodeaten; the greater the proportion of food intake in the morning period, the smallerthe total daily energy intake, as well as the energy intake in the night period. Thesame author has suggested that the morning period is associated with a greaterefficiency of the satiety signal than in the night period, so contributing to a smallerdaily energy intake and the prevention of body mass increase. In the present study,though we did not observe significant correlations between energy intake in themorning and overall intake, a negative correlation was seen between the proportioningested in the afternoon and overall intake, suggesting that afternoon period alsocontributes to a smaller daily energy intake. Furthermore, we observed a positivecorrelation between the proportion ingested at night and overall intake, corroborat-ing directly with de Castro’s findings (2004).

Little is known about the impact that distribution of energy and nutrientsthroughout the day has on body mass regulation. In fact, acute experimentalprotocols have found that the time of day that meals are consumed can promotedifferent metabolic and hormonal responses. So, we support the idea that eating at a‘‘wrong’’ moment can contribute to weight gain and changes in body composition inthe long-term as an adaptation of the body, whereas eating at the ‘‘right’’ momentcan contribute to weight loss and weight gain prevention due to better post-prandial

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response. In this study, although it was a descriptive evaluation, we corroborate withprevious data in the literature, allowing new perspectives for future research. Thefact that we did not observe significant correlations in women remains unknown, butsome differences in postprandial responses between genders (e.g., meal tolerance,that is, the ability of the body to bring blood glucose back to basal levels following ameal because of circadian control) may be present, since there is evidence supportingreduced effective response in women when standard meals are presented, whereasmale subjects’ response is more stable (Ahmed et al. 1976; Nuttall et al. 1985).

Conclusions

Our data indicate that, at least for men, a greater fat intake at night may beassociated with higher %BF, BMI, and WC, whereas food intake in the morningperiod is associated with lower anthropometric variables. Moreover, intake in theafternoon can reduce the total amount ingested for the day, and that intake in thenight can result in greater overall daily intake. Based on these findings, specialattention needs to be given to fat intake in the night period, giving priority to foodintake in the first period of the day, being a positive tool in dietetic planning and apossible anti-obesity complementary strategy for the general population, and nightworkers, that are individuals who have several health disorders associated, in part,with the circadian distribution of food. Further studies, with larger samples, shouldbe developed to better explain these results and with other populations, such as obeseindividuals, since food habits are much modified.

Acknowledgements

The authors thank all volunteers for their participation in the study, Jim Waterhouse, HannaKaren Moreira Antunes, Everald Van Cooler, and Nadine Bressan for their support andassistance, and the support of Associacao Fundo de Incentivo a Psicofarmacologia (AFIP),Centro de Estudos em Psicobiologia e Exercıcio (CEPE), Centro de Estudo Multidisciplinarem Sonolencia e Acidentes (CEMSA), CEPID/SONO-FAPESP (#998/1430373), CNPq(501567/2007-0), CAPES, FAPESP (2009/11056-1), UNIFESP, FADA, and FADA/UNIFESP.

References

Ahmed M, Gannon MC, Nuttall FQ. 1976. Post-prandial plasma glucose, insulin, glucagonand triglyceride responses to a standard diet in normal subjects. Diabetologia. 12:61–67.

Alexander KE, Ventura EE, Spruijt-Metz D, Weigensberg MJ, Goran MI, Davis JN. 2009.Association of breakfast skipping with visceral fat and insulin indices in overweight Latinoyouth. Obesity (Silver Spring). 17:1528–1533.

Arasaradnam MP, Morgan L, Wright J, Gama R. 2002. Diurnal variation in lipoproteinlipase activity. Ann Clin Biochem. 39:136–139.

Arble DM, Bass J, Laposky AD, Vitaterna MH, Turek FW. 2009. Circadian timing of foodintake contributes to weight gain. Obesity (Silver Spring). 17:2100–2102.

Armstrong S. 1980. A chronometric approach to the study of feeding behaviour. NeurosciBiobehav Rev. 4:27–53.

Astrup A. 2001. Healthy lifestyles in Europe: prevention of obesity and type II diabetes by dietand physical activity. Public Health Nutr. 4:499–515.

Baecke JAH, Burema J, Frijters JER. 1982. A short questionnaire for the measurement ofhabitual physical activity in epidemiological studies. Am J Clin Nutr. 36:936–942.

Baecke JA, van Staveren WA, Burema J. 1983. Food consumption, habitual physical activity,and body fatness in young Dutch adults. Am J Clin Nutr. 37:278–286.

Biological Rhythm Research 127

Dow

nloa

ded

by [

McG

ill U

nive

rsity

Lib

rary

] at

11:

00 1

9 N

ovem

ber

2014

Bellisle F, Rolland-Cachera MF, Deheeger M, Guilloud-Battaille M. 1988. Obesity and foodintake in children: evidence for a role of metabolic and/or behavioral daily rhythms.Appetite. 11:111–118.

Bes-Rastrollo M, Martınez-Gonzalez MA, Sanchez-Villegas A, de la Fuente Arrillaga C,Martınez JA. 2006. Association of fiber intake and fruit/vegetable consumption withweight gain in a Mediterranean population. Nutrition. 22:504–511.

Cho S, Dietrich M, Brown CJ, Clark CA, Block G. 2003. The effect of breakfast type on totaldaily energy intake and body mass index: results from the Third National Health andNutrition Examination Survey (NHANES III). J Am Coll Nutr. 22:296–302.

Crispim CA, Zalcman I, Dattilo M, Padilha HG, Edwards B, Waterhouse J, Tufik S, MelloMT. 2007. The influence of sleep and sleep loss upon food intake and metabolism. NutrRes Rev. 20:195–212.

de Castro JM. 2004. The time of day of food intake influences overall intake in humans. JNutr. 134:104–111.

de Castro JM. 2009. When, how much and what foods are eaten are related to total daily foodintake. Br J Nutr. 102:1228–1237.

Dunbar JC, Schultz S, Houser F, Walker J. 1989. Regulation of the hepatic response toglucagon: role of insulin, growth hormone and cortisol. Horm Res. 31:244–249.

Fricker J, Giroux S, Fumeron F, Apfelbaum M. 1990. Circadian rhythm of energy intake andcorpulence status in adults. Int J Obes. 14:387–393.

Geliebter A, Gluck ME, Tanowitz M, Aronoff NJ, Zammit GK. 2000. Work-shift period andweight change. Nutrition. 16:27–29.

Gottlieb DJ, Punjabi NM, Newman AB, Resnick HE, Redline S, Baldwin CM, Nieto FJ.2005. Association of sleep time with diabetes mellitus and impaired glucose tolerance.Arch Intern Med. 165:863–867.

Gregg EW, Cheng YJ, Cadwell BL, Imperatore G, Williams DE, Flegal KM, Narayan KM,Williamson DF. 2005. Secular trends in cardiovascular disease risk factors according tobody mass index in US adults. JAMA. 293:1868–1874.

Holmback U, Lowden A, Akerfeldt T, Lennernas M, Hambraeus L, Forslund J, Akerstedt T,Stridsberg M, Forslund A. 2003. The human body may buffer small differences in mealsize and timing during a 24-h wake period provided energy balance is maintained. J Nutr.133:2748–2755.

Huang CJ, Hu HT, Fan YC, Liao YM, Tsai PS. In press. Associations of breakfast skippingwith obesity and health-related quality of life: evidence from a national survey in Taiwan.Int J Obes (Lond). doi: 10.1038/ijo.2009.285

Ishizaki M, Morikawa Y, Nakagawa H, Honda R, Kawakami N, Haratani T, Kobayashi F,Araki S, Yamada Y. 2004. The influence of work characteristics on body mass index andwaist to hip ratio in Japanese employees. Ind Health. 42:41–49.

Jackson AS, Pollock ML. 1978. Generalized equations for predicting body density of men. BrJ Nutr. 40:497–504.

Jackson AS, Pollock ML, Ward A. 1980. Generalized equations for predicting body density ofwomen. Med Sci Sports Exerc. 12:175–181.

Kant AK, Andon MB, Angelopoulos TJ, Rippe JM. 2008. Association of breakfast energydensity with diet quality and body mass index in American adults: National Health andNutrition Examination Surveys, 1999–2004. Am J Clin Nutr. 88:1396–1404.

Kontogianni MD, Farmaki AE, Vidra N, Sofrona S, Magkanari F, Yannakoulia M. 2010.Associations between lifestyle patterns and body mass index in a sample of Greek childrenand adolescents. J Am Diet Assoc. 110:215–221.

Lennernas M, Akerstedt T, Hambraeus L. 1994. Nocturnal eating and serum cholesterol ofthree-shift workers. Scand J Work Environ Health. 20:401–406.

Lennernas M, Hambraeus L, Akerstedt T. 1995. Shift related dietary intake in day and shiftworkers. Appetite. 25:253–265.

Maffeis C, Provera S, Filippi L, Sidoti G, Schena S, Pinelli L, Tato L. 2000. Distribution of foodintake as a risk factor for childhood obesity. Int J Obes Relat Metab Disord. 24:75–80.

Morikawa Y, Nakagawa H, Miura K, Soyama Y, Ishizaki M, Kido T, Naruse Y, SuwazonoY, Nogawa K. 2007. Effect of shift work on body mass index and metabolic parameters.Scand J Work Environ Health. 33:45–50.

128 M. Dattilo et al.

Dow

nloa

ded

by [

McG

ill U

nive

rsity

Lib

rary

] at

11:

00 1

9 N

ovem

ber

2014

Nuttall FQ, Gannon MC, Wald JL, Ahmed M. 1985. Plasma glucose and insulin profiles innormal subjects ingesting diets of varying carbohydrate, fat and protein content. J AmColl Nutr. 4:437–450.

Patro B, Szajewska H. in press. Meal patterns and childhood obesity. Curr Opin Clin NutrMetab Care. doi: 10.1097/MCO.0b013e32833681a2

Romon M, Edme JL, Boulenguez C, Lescroart JL, Frimat P. 1993. Circadian variation ofdiet-induced thermogenesis. Am J Clin Nutr. 57:476–480.

Russ CS, Ciavarella PA, Atkinson RL. 1984. A comprehensive outpatient weight reductionprogram: Dietary patterns, psychological considerations, and treatment principles. J AmDiet Assoc. 84:444–446.

Schutz Y, Flatt JP, Jequier E. 1989. Failure of dietary fat intake to promote fat oxidation: afactor favoring the development of obesity. Am J Clin Nutr. 50:307–314.

Segal KR, Gutin B, Nyman AM, Pi-Sunyer FX. 1985. Thermic effect of food at rest, duringexercise, and after exercise in lean and obese men of similar body weight. J Clin Invest.76:1107–1112.

Siri WE. 1961. Body composition from fluid space and density. In: Brozek J, Hanschel A,editors. Techniques for measuring body composition. Washington (DC): NationalAcademy of Science.

Song WO, Chun OK, Obayashi S, Cho S, Chung CE. 2005. Is consumption of breakfastassociated with Body Mass Index in US adults? J Am Diet Assoc. 105:1373–1382.

Suwazono Y, Dochi M, Sakata K, Okubo Y, Oishi M, Tanaka K, Kobayashi E, Kido T,Nogawa K. 2008. A longitudinal study on the effect of shift work on weight gain in maleJapanese workers. Obesity (Silver Spring). 16:1887–1893.

Turkoglu C, Duman BS, Gunay D, Cagatay P, Ozcan R, Buyukdevrim AS. 2003. Effect ofabdominal obesity on insulin resistance and the components of the metabolic syndrome:evidence supporting obesity as the central feature. Obes Surg. 13:699–705.

van Amelsvoort LG, Schouten EG, Kok FJ. 1999. Duration of shiftwork related to body massindex and waist to hip ratio. Int J Obes Relat Metab Disord. 23:973–978.

Van Cauter E, Blackman JD, Roland D, Spire JP, Refetoff S, Polonsky KS. 1991. Modulationof glucose regulation and insulin secretion by circadian rhythmicity and sleep. J ClinInvest. 88:934–942.

Waller SM, Vander Wal JS, Klurfeld DM, McBurney MI, Cho S, Bijlani S, Dhurandhar NV.2004. Evening ready-to-eat cereal consumption contributes to weight management. J AmColl Nutr. 23:316–321.

Waterhouse J, Buckley P, Edwards B, Reilly T. 2003. Measurement of, and some reasons for,differences in eating habits between night and day workers. Chronobiol Int. 20:1075–1092.

World Health Organization. 2000. Obesity: preventing and managing the global epidemic.WHO technical report series 894. Geneva: WHO.

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