Childhood overweight and obesity levels continue to be of worldwide concern with the WHO regarding it as a major public health challenge(Reference Nishtar, Gluckman and Armstrong1). European data from 2006 to 2016 indicate that 17·9 % of children aged 2–7 years have overweight and obesity and 5·3 % have obesity, as defined by the International Obesity Task Force criteria(Reference Garrido-Miguel, Oliveira and Cavero-Redondo2). Overweight and obesity rates appear to be stabilising in the Irish childhood population with most recent data estimating that childhood overweight and obesity affect 1 in 5 five-year-olds(Reference Barriuso, Miqueleiz and Albaladejo3–Reference Rito Ana, Buoncristiano and Spinelli5). Evidence of the impact of child sex on rates of overweight and obesity are conflicting. Data from 2016 found no differences in the worldwide rate of increase in overweight and obesity between girls and boys(Reference Rito Ana, Buoncristiano and Spinelli5,Reference Abarca-Gómez, Abdeen and Acosta-Cazares6) ; however, recent data based on Irish children aged 6–7 years old found that girls had higher levels of overweight and obesity than boys (20·4 % girls/13·2 % boys)(Reference Bel-Serrat, Heinen and Murrin7).
Several studies(Reference Chaput, Gray and Poitras8–Reference Chen, Beydoun and Wang10) have examined the relationship between sleep and BMI and BMI z-score in children, with the majority showing that short sleep duration is associated with increased risk of obesity. Fewer studies(Reference Wells, Hallal and Reichert11,Reference Michels, Verbeiren and Ahrens12) have examined body composition measurements such as skinfold measurements, mid upper arm circumference (MUAC) and abdominal circumference (AC). The relationship between inadequate sleep and obesity may be influenced by a number of biological and behavioural pathways. Changes in hormone levels such as leptin and ghrelin(Reference Spiegel, Leproult and L’Hermite-Balériaux13), variations in the type and quantity of food eaten(Reference Bel, Michels and De Vriendt14), physical activity levels(Reference Laurson, Lee and Gentile15) and consequences of various eating behaviour styles have been considered as contributing factors(Reference Miller, Miller and LeBourgeois16).
A child’s eating behaviour will influence the food choice and the amount of food eaten, which consequently can promote overweight and obesity(Reference Mooreville, Davey and Orloski17). Food approach eating behaviours such as food responsiveness and emotional overeating have been associated with obesity risk(Reference McCarthy, Chaoimh and Murray18,Reference Herle, De Stavola and Hubel19) . Eating in the absence of hunger has also been associated with unhealthy BMI and increased adiposity among children(Reference Asta, Miller and Retzloff20). It has been suggested that poor sleep and obesity may be interrelated through eating behaviour(Reference Miller, Miller and LeBourgeois16,Reference Burt, Dube and Thibault21) . Understanding this relationship is vital to better comprehend factors associated with overeating or undereating and thereby help identify strategies for the prevention of childhood obesity(Reference Burt, Dube and Thibault21). Research concerning the underlying association between poor sleep and eating behaviours, such as how a child responds to food, emotional overeating and satiety response, is limited. Poor sleep may result in unhealthy eating habits such as eating when not hungry(Reference Miller, Miller and LeBourgeois16) or eating during times of stress(Reference Lundahl and Nelson22). Poor sleep quality has been found to be associated with higher levels of emotional over-eating and increased food responsiveness(Reference Miller, Miller and LeBourgeois16); thus, sleep duration and quality may influence risk of obesity through specific eating behaviour pathways(Reference Miller, Miller and LeBourgeois16).
However, the development of an unhealthy BMI in childhood is complex and multifactorial. Various influences shape children’s food preferences and eating behaviours potentially predisposing them to unhealthy eating behaviours. Socio-economic status and parental education levels have been shown to influence type and quality of food eaten in childhood(Reference Scaglioni, De Cosmi and Ciappolino23), with socio-economic disadvantage being linked with the development of obesity in childhood and later life(Reference Kininmonth, Smith and Llewellyn24,Reference Mitchell, Bel-Serrat and Stanley25) Environmental considerations such as family setting, parenting style(Reference Podlesak, Mozer and Smith-Simpson26) and parental feeding practices(Reference Kaar, Shapiro and Fell27,Reference Savage, Fisher and Birch28) have all been shown to contribute to the development of eating behaviours in childhood.
Few studies have looked at the role of child sex in the relationship between sleep, eating behaviours and body composition, and results are mixed. A systematic review by Morrissey et al. (Reference Morrissey, Taveras and Allender29) looking at sleep and BMI reported that, out of the 103 articles, in those that alluded to sex differences, nine indicated an association between sleep and overweight or obesity in boys only, whereas three reported an association in girls only. These results suggest that child sex may play a role in how sleep impacts body composition but the mechanism behind this is currently not well understood.
Childhood overweight and obesity not only impact the quality of life and health of the child but can also track into adulthood(Reference Ward, Long and Resch30) potentially influencing longer-term health outcomes(Reference Guh, Zhang and Bansback31). Preventative strategies that tackle modifiable factors such as adequate sleep duration and healthy eating behaviour are paramount in tackling this problem before it manifests.
This study aimed to investigate the association of sleep duration and eating behaviours on body composition in 5-year-old boys and girls. A secondary aim was to determine if the relationship between sleep and BMI is mediated by eating behaviours.
This study presents secondary analysis from the ROLO longitudinal birth cohort study. The original ROLO study was a randomised control trial of a low glycaemic index diet in pregnancy (ROLO study). Details of the ROLO study have been described previously(Reference Walsh, McGowan and Mahony32). In brief, secundigravida women who had previously given birth to a baby weighing over 4 kg were recruited (n 800) from the National Maternity Hospital, Dublin from 2007 to 2011. Mothers were recruited <18 weeks gestation, with a singleton pregnancy, had no previous history of gestational diabetes and were over 18 years old. Mothers were randomised to either the intervention group which received dietary advice on a low glycaemic diet, or the control group who received routine antenatal care. The mothers and children born into this study (n 759) have been followed up as part of the ROLO longitudinal study. Mothers were invited for follow-up when their child turned 5 years old, with 401 mother–child pairs returning at this time point. The current study is cross sectional in design, using data collected at the 5-year follow-up. Early maternal data were used for confounders in the analysis. Maternal education was self-reported and recorded at recruitment for the ROLO pregnancy study. Mothers selected one of the following categories: ‘no schooling’, ‘primary education only’, ‘some secondary level’, ‘complete secondary level’, ‘some third level (certificate/diploma)’ or ‘complete third level (higher-level degree)’.
Ethical approval was obtained from Our Lady’s Children’s Hospital Crumlin (OLCHC) and the National Maternity Hospital (NMH) Ethics Committees (Ethics reference number: GEN/279/12).
All measurements were obtained and calculated by a trained researcher. Mothers and child’s weight (kg) was measured using a calibrated stand-on digital weighing scale (SECA 813) to the nearest 0·1 kg. Participants were measured in light clothing without shoes. Mothers and child’s standing height was measured, without shoes, with head aligned in the Frankfort plain, using a free-standing stadiometer (SECA 217) and measurements recorded to the nearest 0·1 cm. BMI was calculated for mother and child as kg per square metre (kg/m2). BMI z-score was calculated by subtracting the mean and dividing by the standard deviation(Reference Barlow33). For the child, obesity and overweight were categorised using the International Obesity Task Force criteria(Reference Cole, Bellizzi and Flegal34,Reference Cole and Lobstein35) . The child’s head, neck, mid upper arm, chest, abdominal, hip and thigh circumferences were measured using a SECA ergonomic circumference measuring tape, to the nearest 0·1 cm. Skinfold measurements including triceps, biceps, subscapular and thigh were measured using a Holtain Tanner/Whitehouse skinfold callipers to the nearest 0·2 mm. Measurements were recorded three times, and the average was calculated to improve reliability. The sum of skinfolds was calculated by the addition of the four skinfold thickness measurements to act as a marker of overall adiposity.
Sleep was recorded using the Child Sleep Habits Questionnaire, a forty-five-item, validated parental reported questionnaire that assesses sleep habits and sleep problems(Reference Owens, Spirito and McGuinn36). Mothers were instructed to rate the frequency of various sleep habits of a typical week (n 319). Sleep duration was calculated for each child based on usual amount of sleep per night in hours and minutes as reported by mothers and analysed as a continuous variable. Sleep requirements were based on national Health Service Executive guidelines for recommended sleep for 5-year-old children of more than 11 h per night(37).
Eating behaviour assessment
The Children’s Eating Behaviour Questionnaire(Reference Wardle, Guthrie and Sanderson38) was completed by mothers (n 306) to evaluate their child’s eating behaviours. This is a thirty-five-item psychometric tool, which was designed to assess eating behaviour in children(Reference Wardle, Guthrie and Sanderson38). The Children’s Eating Behaviour Questionnaire has been shown to have good internal and external reliability(Reference Wardle, Guthrie and Sanderson38,Reference Sleddens, Kremers and Thijs39) and has been validated against observational measures of eating behaviour(Reference Carnell and Wardle40). Each item response is graded on a five-point Likert scale (‘never to always’) with five items within the Children’s Eating Behaviour Questionnaire being reverse scored. A higher score indicates that the child is more likely to express this eating behaviour. Each question relates to one of eight eating styles which can be classed as either ‘Food approach’ or ‘Food avoidant’. The food approach category includes ‘Food responsiveness’, ‘Enjoyment of food’, ‘Emotional Overeating’ and ‘Desire to drink’. The ‘Food responsiveness’ subscale contains five questions which assess a child’s appetite and whether they display a heightened response to external food cues. The ‘Enjoyment of food’ subscale consists of four questions assessing a child’s enjoyment and interest in food. The ‘Emotional overeating’ subscale contains four questions, which explore overeating as a reaction to negative emotions such as annoyance, worry, anxiety or boredom. The ‘Desire to drink’ subscale contains three questions assessing an increased desire for frequent beverage consumption. The ‘Food avoidant’ category includes ‘Food fussiness’, ‘Emotional undereating’, ‘Slowness in eating’ and ‘Satiety responsiveness’. The ‘Food fussiness’ subscale includes six questions that assess food avoidance, selectivity and a lack of interest in food. ‘Emotional undereating’ is assessed by four questions, exploring a child’s inclination to limit food intake in times of negative and positive emotions, such as being upset, sad, happy or tired. ‘Slowness in eating’ comprises four questions pertaining to the length of time a child takes to finish their meal, indicating a lack of interest in eating. The ‘Satiety responsive’ subscale consists of five questions, exploring a child’s inability to respond to internal satiety cues and reduction in intake due to perceived fullness. In the current sample, Cronbach’s α for the Children’s Eating Behaviour Questionnaire ranged from 0·695 to 0·928; thus, all questions were included in the analysis.
Statistical analysis was performed using Statistical Package for Social Sciences (version 24, IBM). The distribution and normality of continuous variables were determined by visual inspection of histograms and Q-plots. Mean and standard deviation were reported for normally distributed data with median and interquartile range reported for non-normal data. Independent t tests for normally distributed data were used to examine differences in body composition, eating behaviours and sleep duration between boys and girls. χ 2 tests were used to determine differences between boys and girls regarding BMI category, maternal education level and whether children met sleep requirements or not. Multiple linear regression analysis was performed on the full cohort of children and also stratified by sex. All analysis was adjusted for maternal education level, maternal BMI at the 5-year follow-up, original randomised control trial allocation group, child age at 5-year-old visit and whether the child had been breastfed or not. Mediation analysis was completed to determine whether the relationship between sleep and BMI is mediated by eating behaviours. The sum of the means of each of the four food approach subscales (‘Enjoys food’, ‘Emotional overeating’, ‘Desire to drink’ and ‘Food responsiveness’) was calculated to create the ‘Mean food approach’ variable. A ‘Mean food avoidant’ variable was obtained from the sum of the means of the four food avoidant subscales (‘Food fussiness’, ‘Emotional undereating’, ‘Slowness in eating’ and ‘Satiety responsiveness’). In the mediation models, sleep duration was the independent variable, child BMI the dependent variable and ‘Mean food approach’ or ‘Mean food avoidant’ were the mediators. Mediation analysis was performed using PROCESS macro for Statistical Package for Social Sciences version 3.5(Reference Hayes41). PROCESS for Statistical Package for Social Sciences uses a bootstrap approach to determine the significance of mediation effects(Reference Preacher and Hayes42). This analysis estimates if the indirect effect of the independent variable (sleep) on the dependent variable (BMI) through the mediating variable (eating behaviours) is equivalent to the total effect of the independent variable on the dependent variable, minus its direct effect. Bootstrapped CI at 95 % were used for 1000 resamples to test if the indirect effect of sleep duration on BMI was mediated through either ‘Mean food approach’ or ‘Mean food avoidant’ eating behaviours. Mediation occurred if the CI of the indirect effect did not include 0. Mediation analysis was conducted with and without confounders, as described above.
Descriptive statistics of the mother–child pairs are presented in Table 1. Child mean age was 5·1 years old, with a mean BMI of 16·2 kg/m2. Using the International Obesity Task Force cut-offs for BMI(Reference Cole, Bellizzi and Flegal34), it was determined that 15·1 % and 8·9 % of children were categorised as having overweight or obesity, respectively. Body composition measures, eating behaviours and sleep duration variables were considered normally distributed; therefore, parametric tests were used. Girls had higher skinfold thickness measurements and higher mean scores for MUAC than boys. Sixty-one percentage of children met Irish Health Service Executives sleep recommendations of 11 h or more per night for 5-year-olds. Boys had higher mean scores for food fussiness than girls (P = 0·001). Associations between sleep duration (hours) and body composition for the full group are shown in online Supplementary Table 1. A 1-h greater sleep duration was associated with 0·24 kg/m2 (95 % CI –0·42, –0·03, P = 0·026) lower BMI, 0·13 sd (95 % CI –0·26, –0·01, P = 0·038) lower BMI z-score and 0·21 cm (95 % CI –0·410, –0·015, P = 0·035) lower MUAC. When the group was stratified by child sex (Table 2), an inverse association was found between sleep duration and BMI (kg/m2) (B = –0·32; 95 % CI –0·60, –0·04, P = 0·024), BMI z-score (B = –0·18, 95 % CI –0·35, –0·02, P = 0·029) MUAC (cm) (B = –0·29, 95 % CI –0·58,0·01, P = 0·050) and AC (B = –1·10, 95 % CI –1·85, –0·21, P = 0·014) in girls only.
* International Obesity Task Force age- and sex-specific BMI cut-offs for defining weight status in children 2–18 years; P-value from Independent t tests for differences between boys and girls; P-value from χ 2 test for differences in BMI category, met sleep requirements and maternal education level between boys and girls. Mean food approach refers to the sum of the means of the four food approach eating behaviours (Food Responsive, Emotional Overeating, Enjoys Food, Desire to Drink). Mean food avoidant refers to the sum of the means of the four food avoidant eating behaviours (Satiety Response, Emotional Undereating, Slowness Eating, Food Fussiness); Statistically significant (P < 0·05).
SF, skinfold thickness; Sum of skinfolds, Triceps, Subscapular, Thigh; MUAC, mid upper arm circumference.
* Multiple linear regression models adjusted for maternal BMI, breastfed ever, child age, control v. non-control, maternal education; statistically significant (P value < 0·05).
Multiple linear regression analysis to examine associations between children’s eating behaviour and body composition was stratified by child sex as summarised in Table 3. Both girls and boys showed a positive association between ‘Enjoys food’ and BMI and MUAC. Significant positive associations were seen in girls only, between ‘Food responsiveness’ and BMI (kg/m2) (B = 0·09, 95 % CI 0·36, 2·21, P = 0·007), MUAC (cm) (B = 0·07, 95 % CI 0·01, 0·12, P = 0·018) and AC (B = 0·20, 95 % CI 0·04, 0·35, P = 0·016). Associations were also found between ‘Mean food approach’ and BMI (B = 0·20, 95 % CI 0·09, 0·31, P ≤ 0·001), MUAC (B = 0·157, 95 % CI 0·040, 0·274, P = 0·009) and AC (B = 0·41, 95 % CI 0·07, 0·74, P = 0·018) in girls. A negative association between ‘Food fussiness’ and BMI (B = –0·05, 95 % CI –0·08, –0·007, P = 0·020) and AC (B = –0·14, 95 % CI –0·27, –0·004, P = 0·043) was found in boys only. Similarly, a negative association was only seen in boys between ‘Mean food avoidant’ and BMI and AC (B = –0·089, 95 % CI –0·17, –0·01, P = 0·028; B = –0·31, CI –0·58, –0·03, P = 0·029). Results for the whole group are summarised in online Supplementary Table 2.
SF, skinfold thickness; Sum of Skinfolds, Biceps, Triceps, Subscapular, Thigh; MUAC, mid upper arm circumference.
* All multiple linear regression models controlled for maternal BMI, breastfed ever, control v. non-control, maternal education, child age; mean food approach refers to the sum of the means of the four food approach eating behaviours (Food Responsive, Emotional Overeating, Enjoys Food, Desire to Drink). Food Avoidant refers to the sum of the means of the four food avoidant eating behaviours (Satiety Response, Emotional Undereating, Slowness Eating, Food Fussiness); statistically significant (P < 0·05).
We found no strong associations between sleep duration and any of the eating behaviours for the full group (online Supplementary Table 3). When stratified by sex, a negative association between sleep duration and ‘Emotional undereating’ (B = –0·68, 95 % CI –1·34, –0·02, P = 0·045) was observed in girls (Table 4). The CI for the association between sleep duration and food fussiness for boys spanned the null value; however, the unstandardised coefficient B and CI demonstrate some clinical significance (B = –1·35, CI –2·72, 0·0009, P = 0·052), in that every 1 h more of sleep was associated with a 1·35-point decrease in food fussiness score (Table 4).
* All multiple linear regression models adjusted for maternal BMI, breastfed ever, child age, control v. non-control, maternal education; mean food approach refers to the sum of the means of the four food approach eating behaviours (Food Responsive, Emotional Overeating, Enjoys Food, Desire to Drink). Mean food avoidant refers to the sum of the means of the four food avoidant eating behaviours (Satiety Response, Emotional Undereating, Slowness Eating, Food Fussiness); statistically significant (P value < 0·05).
Mediation analysis was performed to determine if eating behaviours mediated the relationship between sleep duration and BMI. Examining sleep as the independent variable, BMI as the dependent variable and ‘Mean food approach’ as the mediator, no relationship between sleep duration and ‘Mean food approach’ was observed. Therefore, these results did not meet conditions required for mediation analysis (online Supplementary Fig. 1). Supplementary Fig. 2 presents the analysis using ‘Mean food avoidant’ as the mediator between sleep duration and BMI. The association between sleep duration and ‘Mean food avoidant’ was not significant (B = –0·43, 95 % CI –0·86, 0·06, P = 0·05). Sleep duration was associated with lower BMI kg/m2 (B = –0·07, 95 % CI –0·14, –0·03, P = 0·003); however, there was no evidence of a relationship between sleep duration and BMI (direct effect) in the model that included ‘Mean food avoidant’ (B = –0·20, 95 % CI –0·40, 0·01, P = 0·06). The indirect effect was not statistically significant as it included 0 (B = 0·04, 95 % CI –0·004, 0·101, P = 0·03). This analysis suggests that both ‘Mean food approach’ and ‘Mean food avoidant’ eating behaviours did not mediate the relationship between sleep duration and BMI. Addition of confounders to the mediation models gave similar results; therefore, results are described without confounders.
The current study found inverse associations between sleep duration and body composition, specifically BMI, BMI z-score, MUAC and AC. Associations were also found between eating behaviours and body composition for the whole group and when stratified by sex. There was also some evidence of associations between sleep duration and food avoidant eating behaviours, although some results spanned the null. Eating behaviours did not mediate the relationship between sleep duration and BMI.
Our results concur with previous childhood studies that support short sleep duration being associated with increased risk of childhood obesity(Reference El-Sheikh, Bagley and Keiley43–Reference Shi, Taylor and Gill45). Sleep duration is most often reported as demonstrating an inverse relationship with BMI and BMI z-score(Reference Ekstedt, Nyberg and Ingre46,Reference Carter, Taylor and Williams47) . Our analysis showed that a 1-h greater sleep duration was associated with 0·21 cm lower MUAC. Although MUAC is typically used to identify undernutrition and low fat-free mass, there is emerging evidence that a strong linear relationship between MUAC and weight status exists(Reference Talma, van Dommelen and Schweizer48–Reference Craig, Bland and Ndirangu50). As well as MUAC, few studies have examined the relationship between sleep duration and skinfold thicknesses(Reference Wells, Hallal and Reichert11). We found that 1 h more of sleep was associated with a potential reduction of 1·18 mm in sum of skinfold thickness (95 % CI –3·05, 0·69), though results spanned the null value. Our results indicate that decreased sleep duration is a factor not only influencing BMI and BMI z-score but also impacting body composition and adiposity markers in young children.
Interestingly, when our sample was stratified by child sex, inverse associations between sleep duration and BMI, BMI z-score, MUAC and AC were observed in girls only. Other studies have demonstrated that sex affects the relationship between sleep duration and obesity, but research is limited and results conflicted as to which sex is most affected: girls(Reference El-Sheikh, Bagley and Keiley43,Reference Cao, Zhu and He51) or boys(Reference Chen, Beydoun and Wang10,Reference Laurson, Lee and Gentile15,Reference Larsen, Sleddens and Vink52) . These inconsistent results suggest that different aetiological mechanisms may be underlying the relationship between sleep and obesity across the sexes relating to hormone regulation such as leptin or ghrelin, variations in physical activity levels, energy imbalances, eating behaviours and pubertal influences(Reference Morrissey, Taveras and Allender29,Reference El-Sheikh, Bagley and Keiley43,Reference Cao, Zhu and He51,Reference Larsen, Sleddens and Vink52) . A potential reason for differences seen between boys and girls in our cohort could be that girls who are deprived of sleep will spend less time engaged in physical activity(Reference Cao, Zhu and He51) and this may predispose them to increased sedentary behaviours, thus creating a positive energy balance. The concurrent influence of inadequate sleep, low physical activity and high levels of screen time in children aged 7–12 years old has been shown to increase obesity risk(Reference Laurson, Lee and Gentile15).
There is growing evidence that one of the main pathways in which inadequate sleep influences weight gain is through increased food intake and increased vulnerability to eat(Reference Chaput53,Reference St-Onge54) . To date, the majority of research in this area has been with adults. Results have pointed to factors such as increased periods of wakefulness providing more opportunity to eat, a greater demand for energy to sustain the longer periods of being awake and increased predisposition to snacking behaviour, as possible explanations of increased dietary intake(Reference Chaput53,Reference Chaput, Klingenberg and Astrup55) . An experimental study in school-age children demonstrated that children who had an increase in average nightly sleep of 2 h, 21 min resulted in a lower energetic intake and lower weight than those with shorter sleep duration(Reference Hart, Carskadon and Considine56). Previous studies have indicated that changes in leptin and ghrelin levels may be influenced by sleep deprivation and thus impact appetite and satiety responses(Reference Spiegel, Leproult and L’Hermite-Balériaux13,Reference Taheri, Lin and Austin57) . However, findings from these early studies have not been replicated(Reference Chaput and St-Onge58). There is also limited research available as to whether the effect of short sleep duration on leptin and ghrelin is specific to sex(Reference Storfer-Isser, Patel and Babineau59). If hormonal influences are not the main driving force behind increased food intake, specific eating behaviours may offer some explanation. Our findings are similar to previous research that observed a link between food approach eating behaviours and childhood adiposity(Reference Clairman, Dettmer and Buchholz60–Reference Spence, Carson and Casey63). Behaviours such as food responsiveness reflect a child’s tendency to want and enjoy food(Reference Boswell, Byrne and Davies64). Poor response to internal satiety cues or over-responsiveness to external food signals such as the presence or smell of foods are implicated in higher energy intakes and subsequent risk of overweight/obesity(Reference Wardle, Guthrie and Sanderson38,Reference Carnell and Wardle40,Reference Jansen, Theunissen and Slechten62) . Preschool children with higher food approach eating behaviour scores have been shown to be at risk of higher weight status with significant differences been found between weight status groups for ‘food responsiveness’, ‘enjoyment of food’, ‘emotional overeating’ and ‘satiety responsiveness’(Reference Spence, Carson and Casey63). The reasons girls may differ to boys in relation to food approach eating behaviours and body composition as we observed have not been explored widely. Whilst previous studies have controlled for child sex(Reference Webber, Hill and Saxton61,Reference Viana, Sinde and Saxton65) , few have examined the effect of sex separately.
Variation in genetic activity between boys and girls could contribute to both children’s weight status and their susceptibility to eating in response to the presence of foods(Reference Kral and Faith66). Genetics may also impact eating behaviour directly or indirectly through environmental influences such as parental modelling of the child’s eating behaviour(Reference Kral and Faith66). Parental feeding strategies are strongly influential in how and what a child will eat. Several studies have shown that repeated exposure to a variety of foods in infancy will lead to a broader acceptability of foods during weaning and in later childhood(Reference Maier-Nöth, Schaal and Leathwood67,Reference Anzman-Frasca, Savage and Marini68) . Parental style of feeding is also influential on a child’s development of feeding behaviour. Feeding practices such as excessive parental control, pressuring to eat or using rewards to encourage feeding have all been shown to affect a child’s eating behaviour(Reference Jansen, de Barse and Jaddoe69–Reference Blissett, Meyer and Haycraft71). Furthermore, differences have been demonstrated in the type of feeding style used by a parent between male and female children(Reference Blissett, Meyer and Haycraft71). Another important consideration when exploring the development of eating behaviours in childhood and risk of obesity is how available or accessible food is within the home(Reference Haines, Haycraft and Lytle72). It has been demonstrated that the type of food and drink available in the home environment, such as lower fruit and vegetable sources or higher sugar-sweetened beverage availability, is associated with obesity risk and less healthy dietary patterns(Reference Couch, Glanz and Zhou73,Reference Ding, Sallis and Norman74) . Lower income families, due to multiple jobs or shift work, may be away from home at irregular or longer intervals which may impact whether meals are prepared at home or not(Reference Bauer, Hearst and Escoto75). When considering childhood obesity risk, it is crucial to reflect on the complex influence family environment has on shaping childhood eating behaviours. Further exploration is warranted in relation to how family environmental factors impact differs between boys and girls.
Our cohort of boys presented with significantly higher scores for food fussiness than girls. In addition, inverse associations between food avoidant eating behaviours and body composition markers were observed in boys only. Evidence is conflicting regarding the impact of food avoidant eating behaviours such as fussy eating on weight status. Some previous research has reported negative associations between food avoidant eating behaviours and childhood adiposity and obesity tendencies(Reference Spence, Carson and Casey63,Reference Viana, Sinde and Saxton65,Reference Parkinson, Drewett and Le Couteur76,Reference Antoniou, Roefs and Kremers77) , whilst others have demonstrated no relationship(Reference Finistrella, Manco and Ferrara78,Reference Jiang, Yang and Zhang79) . Children with food avoidant eating behaviours typically limit fruit and vegetables within their diet which may lead to poorer overall quality of diet and increased intake of more energy-dense foods, which could in turn contribute to overweight and obesity. Alternatively, food avoidant eating behaviours may negatively affect a child’s growth and development due to poor weight gain or nutritional status as a consequence of inadequate intake. Our findings show negative associations between food avoidant eating behaviours and boy’s body composition, whereas food approach behaviours were more strongly positively associated with girl’s body composition. Early assessment of childhood eating styles could prove useful in identifying those who are susceptible to unhealthy weight gain or those at risk of poor growth. Childhood obesity commonly tracks into adulthood; therefore, early intervention to prevent the manifestation of eating behaviours known to be associated with unhealthy body weight is fundamental in curtailing further increases in obesity.
Inadequate or poor-quality sleep may drive behavioural and physiological changes that consequently affect eating behaviour(Reference Miller, Miller and LeBourgeois16). This relationship could be bidirectional in that eating behaviours may have a causal role in contributing to poor or inadequate sleep. Contrary to expectations, we found no significant associations between food approach eating behaviours and sleep duration (Table 4). In addition, food approach eating behaviours did not mediate the relationship between sleep duration and BMI. In contrast to our findings, previous work has demonstrated that poor sleep quality and duration may influence risk of obesity through certain eating behaviour pathways(Reference Miller, Miller and LeBourgeois16,Reference St-Onge54) . Our differing results may be explained by age differences or socio-economic background between cohorts. Of interest in our results was that sleep duration was inversely associated with food fussiness in both sexes. In boys, who in this cohort had higher scores for food fussiness than girls, 1 h more sleep was associated with 1·3 points reduction in food fussiness score, although the CI spanned the null. This finding requires further exploration as improved sleep could offer benefits in the treatment or prevention of food fussiness, which could be easily incorporated into advice and resources used to help parents and caregivers address this behaviour.
In the present study, we demonstrated that both short sleep duration and some eating behaviours were associated with body composition in 5-year-old children. However, neither food approach nor food avoidant eating behaviours mediated the relationship between sleep duration and BMI. Our results demonstrated differences between boys and girls, in the relationship between sleep duration and body composition and in the relationship between eating behaviours and body composition, suggesting that distinctive underlying mechanisms may be at play between the sexes.
Increasing our understanding of what specifically drives the development of obesity in relation to child sex would offer benefits both clinically and in the public health setting. This knowledge could help in the planning of effective obesity prevention initiatives and enable the provision of targeted support and resources for parents and caregivers. Clear advice about a child’s sleep requirements and potential barriers to achieving adequate sleep should be available for health care providers, parents and caregivers. At 5 years old, our cohort is at a crucial age to tackle unhealthy weight gain before it becomes an embedded problem.
Further investigations are warranted to better understand our perceived sex differences in relation to what the pathways are involved in the sleep and obesity connection and the influence of eating behaviours on this. As we continue to study this same cohort at their 9–11-year-old follow-up, the availability of longitudinal data will help us to clarify our findings.
The strengths of the current study include the use of validated child sleep and eating behaviour questionnaires, accurate objective anthropometry and body composition measurements. We included several body composition parameters to allow assessment of both weight status and body adiposity as fat distribution has been associated with cardiovascular risk and obesity in young children(Reference Ong, Ahmed and Emmett80). The present study has a number of limitations. It is exploratory in design; thus, power and sample size calculations were not included for this secondary analysis. Loss to follow-up of the study population may have resulted in selection bias. The sample included a high proportion of mothers who had achieved tertiary or higher education level which has previously been shown to be associated with being more likely to participate in research(Reference O’Brien, Alberdi and Geraghty81). As per the selection criteria for the original randomised control trial, all children were second born children whose older sibling was macrosomic at birth. This may have resulted in a cohort who are potentially obesogenic. Data on sleep, children’s eating behaviours and body composition were all measured at 5 years old; therefore, the cross-sectional nature of this study limits the ability to establish the direction of the relationships found or assess causality. Future studies with sufficient power are required to allow us to further investigate associations between sleep, eating behaviours and body composition. Although important potential confounders were included in this analysis, other potential confounders such as physical activity levels and screen time exposure which are known to be important contributors to childhood obesity risk would be important for inclusion in future analyses. Family environmental factors such as parental feeding style, parental feeding behaviours, family income and food availability all play a role in eating behaviour and weight status. Other limitations include that sleep is measured via mother’s self-report which may lead to inaccurate reporting of sleep duration. A more objective method of measuring sleep such as actigraphy would strengthen our findings. We examined sleep duration in this study; however, the inclusion of factors such as sleep efficiency, timing and quality should be considered as part of the relationship between sleep and obesity(Reference Morrissey, Taveras and Allender29).
This analysis found associations between sleep duration and body composition parameters and associations between eating behaviours and body composition. Further exploration into the link between sleep duration and eating behaviours and how that affects body composition is warranted. At age 5, both prevention of obesity and ensuring adequate growth using modifiable factors such as instilling healthy sleep patterns and eating behaviours are paramount. Public health messages that provide clear and uniform guidelines on sleep recommendations would support parents and caregivers. Development of concise screening questions could assist health care professionals to assess children’s eating behaviours and sleep patterns. Further research is needed to clarify age and sex-specific effects in the relationship between sleep and body composition, and what role of eating behaviours on play on this. What factors might be protective for girls in preventing unhealthy weight or body composition needs further investigation. Analysis using longitudinal data is warranted to investigate the long-term relationship and direction in the associations between sleep, eating behaviours and body composition.
The authors would like to thank all the ROLO participants for their involvement and all the staff of the National Maternity Hospital and the Perinatal Research Centre.
This study was supported by the Health Research Board, Ireland, the Health Research Centre for Health and Diet Research, The National Maternity Hospital Medical Fund and the European Union’s Seventh Framework Programme (FP7/2007–2013), project Early nutrition under grant agreement no. 289346. Children’s Hospital Foundation, Tallaght & the National Childrens Research Centre.
F. M. McA. was responsible for the project conception; A. D., F. M. McA., M. C. C., J. M., C. McD., S. L. OR., L. M. OK., and P.M. K. designed the research and analysis plan; J. M. collated the database; A. D. analysed the data and performed statistical analysis; A. D. wrote the paper and all other authors reviewed and approved the final manuscript.
There are no conflicts of interest.
For supplementary material referred to in this article, please visit https://doi.org/10.1017/S0007114521002725