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European Journal of Clinical Nutrition (1997) 51, 443±448 ß 1997 Stockton Press. All rights reserved 0954±3007/97 $12.00 Diet composition and body mass index in pre-school children PSW Davies1,2 1 School of Human Movement Studies, Faculty of Health, Queensland University of Technology, Kelvin Grove Campus, Red Hill, Queensland, 4059, Australia; and 2Infant and Child Nutrition Group, Dunn Nutrition Unit, Downhams Lane, Milton Road, Cambridge CB4 1XJ, UK Objective: To investigate the relationship between diet composition and body mass index (BMI) in pre-school children. Design: Reanalysis of data from the National Diet and Nutrition Survey of children aged 1.5±4.5 y. Height and weight of children were used to calculate Body Mass Index (BMI) and BMI standard deviation scores. Dietary intake data were used to calculate percentage of total energy intake derived from fat, carbohydrate and protein. These data were then divided into quintiles. The data were then analysed in order to assess if there was any relationship between the diet composition and BMI. Setting: Community based project throughout Great Britain. Subjects: 1444 children aged 1.5±4.5 y. Measurements: Diet composition was assessed in terms of percentage energy derived from fat, protein and carbohydrate following a four day weighed intake carried out by the parents or carers of the child. Body size was assessed by measuring BMI and calculating the standard deviation score relative to UK reference data. Results: There were no trends apparent using ANOVA and multiple regression that indicated that diet composition was related to body size. Conclusions: In a large cohort of pre-school children we are unable to con®rm the recent ®ndings in much smaller samples that diet composition affects body size. Other factors such as energy intake per se and levels of habitual physical activity might have a more important bearing on BMI in pre-school children. Descriptors: children, body mass index, obesity, diet composition Introduction It is accepted that obesity is a hazard to health. Moreover, obesity is now prevalent enough to be considered as one of the most important public health and medical problems of recent years (Prentice & Jebb, 1995; Garrow, 1992; ). The last of these three publications highlights the UK Government's aim to reduce the percentages of men and women aged 16±60 y who are obese by at least 25% for men and at least 33% for women by 2005, that is to reduce the prevalence from 8%±6% in men and from 12%±8% in women. A number of studies have related obesity in adulthood to obesity in childhood (Poskitt & Cole, 1977; Eid, 1970; Durnin & McKillop, 1978; Rolland-Cachera et al, 1987), and the conclusion that can be drawn from these investigations is that many overweight or obese children become overweight or obese adults. Thus the aetiology of obesity in childhood is important to the study and implications of obesity in later life. The accumulation of excess body fat is dependant on a change in the fundamental energy balance equation, namely energy intake energy expenditure energy stored. An increase in energy stored, as fat, can lead to obesity, and a number of mechanisms can contribute to an increase in stored energy. Some work in this ®eld (Johnson et al, 1956; Hampton et al, 1967; Baecke et al, 1983) suggested that obese children did not consume more calories than their leaner peers and this led to suggestions that a reduced Correspondence: Dr PSW Davies. Received 17 December 1996; revised 5 March 1997; accepted 14 March 1997 basal metabolic rate was a cause of obesity. However, subsequent studies (Southgate, 1986) have suggested that there is no fundamental reduction in basal metabolic rate which is responsible for the development of obesity. This area is still controversial with recent data suggesting a role for a low resting metabolic rate in the development of obesity (Astrup et al, 1995). Attention has also focused on the energy intake side of the energy balance equation. A very straightforward, but possibly simplistic argument can be put forward which reasons that, if energy intake is in excess of energy expenditure and hence requirements, energy stored will increase and hence there will be an increase in body fat potentially leading to obesity. This argument however fails to consider that the composition of the diet might have an in¯uence on the metabolism of energy by the body. There is now mounting evidence that diet composition is related to body size. For example, there are numerous animal studies (Hill, 1990; Hill et al, 1989; Hill et al, 1983; Triscari et al, 1985; Lucas et al, 1989; Herberg et al, 1974; Jen, 1988; Levin et al, 1986; Oscai et al, 1984; Oscai et al, 1987) that show that a high fat diet induces obesity. Some such studies that used iso-calori®c diets differing in fat and carbohydrate content offer compelling evidence that diet composition is of importance in the aetiology of obesity, at least in animal models. A number of studies in adult humans (Dreon et al, 1988; Kromhout et al, 1988; Romieu et al, 1988; Miller et al, 1990; Tucker & Kano, 1992) have suggested that diets high in fat caused body fat levels to increase and diets high in carbohydrate are associated with lower levels of body fat. Carefully controlled studies that manipulate the diet also lend weight to the argument that diet composition is Diet composition and BMI in pre-school children PSW Davies 444 important in weight maintenance and can in¯uence body composition (Lissner et al, 1987; Kendall et al, 1991; Prewitt et al, 1991). It has been postulated that in adults a high fat diet leads to the deposition of body fat due to the ef®ciency of the conversion of dietary fat into stored triglyceride. The metabolic cost of such a conversion is in the order of 3% of energy intake whereas the cost of storing dietary carbohydrate as body fat requires the expenditure of 23% of the ingested energy (Flatt, 1985). Again, in adults it has been suggested that resting metabolic rate and the thermic effect of food differ according to diet composition, in that there is more potential for a thermogenesis effect following a high carbohydrate low fat meal (Sims & Danforth, 1987). Some animal work (Landsberg & Young, 1983) has shown that sympathetic nervous activity is increased following a high fat meal and such changes might in¯uence some of the changes in energy output and adaptive thermogenesis that follow with changes in daily intake. Differences in enzyme response to diet composition have been implicated in the relationship between diet composition and body composition. Speci®cally, high levels of dietary fat have been found to be directly related to levels and activity of lipoprotein lipase, the major rate limiting enzyme for the conversion of dietary lipids in stored lipid. Finally, there is evidence to suggest that in some individuals there is a blunted post meal response to high fat intakes, and that reduced post meal fat oxidation leads to an increase in body size and potential obesity. To date however, there has been limited investigation of the effect of those possible phenomena in children (Gazzaniga & Burns, 1993; Rolland-Cachera et al, 1995; Oretega et al, 1995). In the ®rst of these studies a signi®cant positive correlation was found between percentage energy intake derived from fat and percentage body fat in a group of 48 children aged 9±11 y. However, in a subgroup of obese children (n 18), the correlation was not signi®cant. The second study found that the only nutrient intake in early childhood that was correlated with later BMI was percentage energy intake derived from protein. Again this study was of relatively few children (n 112). Finally, in a cohort of sixty four adolescents divided into obese and nonobese groups based on their BMI despite there being difference in energy intake per se, the obese group derived a greater proportion of their energy from protein and fat. Thus there currently con¯icting reports from studies using small sample sizes. Nevertheless the phenomenon of diet composition being related to body size would be of major importance if proved to be true. The recently completed National Diet and Nutrition Survey (NDNS) of children aged 1.5±4.5 y (Gregory et al, 1995) provides the opportunity to investigate this potential phenomenon in a large group of pre-school children. Subjects and methods Subjects The NDNS required that a nationally representative sample of pre-school children be recruited. The initial aim was to recruit 1500 children evenly distributed across the age range 1.5±4.5y. The sample was selected using a multistage random probability design, with postal sector as ®rst stage units. The small user Post Code Address ®le was used as the sampling frame. The frame was strati®ed by region. A total of 100 postal sectors were selected. From each postal sector 280 addresses were randomly selected. To identify households which contained an eligible child, namely a child aged between 1.5 and 4.5 y, each address was sent a sift form which asked for details of the sex and date of birth of all people living in the household. From returns, households containing an eligible child were identi®ed. Only one eligible child from each household was selected. Assessment of diet The parent or carer of the child was asked to keep a weighed record of all food and drink consumed by the child, both in and out of the home, over four consecutive days including a Saturday and Sunday. Parents were given a set of calibrated Soehnle Quanta scales and two recording documents; one for food eaten within the home and another for use when foods could not be weighed, that is foods eaten away from the home. Instructions on how to complete the four day record were left with the parent or carer along with instructions on how to weigh and record leftovers, and food that was spilt or not eaten which could not be reweighed. Folowing coding of the diaries by ®eldworkers, the dietary record was linked to a nutrient database and nutrient intakes calculated from quantity of food consumed. The nutrient database which was compiled by the Ministry of Agriculture, Fisheries and Food, holds information on 54 nutrients for each food coded. The quantity of food energy derived from fat, carbohydrate and protein was expressed both in grams per day and as a percentage of total energy intake. Before accepting completed four day records, a number of checks were carried out. Firstly, checks were carried out to identify cases where the weight of a speci®c food consumed was outside of a speci®ed expected range. Any such cases were individually evaluated and errors corrected. Secondly, checks were carried out to identify cases where any speci®c nutrient was outside of an expected range. In the case of most nutrients a maximum value was the only one that could be speci®ed. Ranges were provided by the Ministry of Agriculture, Fisheries and Food. This method for evaluating dietary intake has been previously assessed in the same age group via a comparison between estimates of energy intake from a 4 d weighed intake with measures of total energy expenditure using the doubly labelled water technique (Davies et al, 1994). The mean measurements of energy intake and expenditure were extremely close. The average difference of only 3% provided suf®cient con®dence in the weighed intake methodology for it to be used in the major nationwide survey from which the data in this present study derives. Assessment of body size The nature of the design of the NDNS with many areas and ®eldworkers restricted the extent of the anthropometry that could be undertaken. Nevertheless, height and weight were recorded where possible. In children aged 2 y or more, stature was measured using a portable modi®ed digital telescopic stadiometer designed by the Of®ce of Population Censuses and Surveys (Gregory et al, 1995). In younger children supine length was measured using the same equipment. Measurements were taken to the nearest millimetre. Body weight was measured with the child wearing minimal clothing using Soehnle Quantratonic digital personal weighing scales. The measurement was recorded to 100 g. Diet composition and BMI in pre-school children PSW Davies A summary of the dietary intake data is shown in Table 2. There was a signi®cant difference between mean energy intake in the boys and girls (t 4.92, P < 0.01). Also the girls consumed more energy from protein and less from carbohydrate than the boys (t 2.27, P < 0.05; t 2.22, P < 0.05) respectively. There was no signi®cant difference in percentage energy from fat between the boys and girls. The boys consumed signi®cantly more carbohydrate, protein and fat in absolute terms than the girls. In a similar analysis to that of Bolton±Smith and Woodward (1994) the intake data for each sex has been divided into ®fths. In each ®fth therefore there are approximately 145 children. Figures 1 and 2 show the mean BMI SDS 2 s.e. of mean of the children that fell within each of the intake ®fths for percentage energy derived from carbohydrate, fat and protein. In the boys the mean BMI SDS in every ®fth is above 0 but this simply re¯ects the fact that mean BMI SDS for the entire cohort of boys is 0.30. Similarly for the entire cohort of girls the mean BMI SDS is 70.14 and subsequently, the mean BMI SDS values in the different ®fths for the girls are also generally negative. Analysis of variance revealed no difference across quintiles in mean BMI SDS, in either boys or girls and it is clear that there are no obvious trends for BMI SDS within the analysis of carbohydrate, fat and protein intake. Nevertheless, it has been suggested (Saimon & Flatt, 1985) that within groups determined by the percentage energy derived from different nutrients while the mean BMI SDS may be similar the distribution of BMI SDS becomes more positively skewed as the percentage energy from fat increases. In order to investigate this we have calculated the percentage of children whose BMI SDS is above 1.5 (about the 93rd percentile) in each ®fth of intake. These results are shown in Table 3. Again, no trend is apparent with between about 6% and 13% of children having BMI SDS greater than 1.5 within the different ®fths of intake. Finally results of a multiple regression with BMI SDS as the dependant variable and per cent energy from protein, carbohydrate and fat as independent variables are shown in Table 4. Again there is no signi®cant association between Height and weight together allow the calculation of BMI (weight/height2). BMI is a good index of body size and has been used for many years to assess the level of overweight and underweight in adults (Khosla & Lowe, 1967; Garrow & Webster, 1985) and in children (Cole et al, 1981; Rolland-Cachera et al, 1982; Matteis et al, 1993). However, in childhood as mean BMI changes markedly with age, rising rapidly in infancy, then falling to a nadir at about 6 y of age and then rising again through to adulthood, BMI needs to be assessed using age-related references and such data has been recently published (Cole et al, 1995). These new data also allow for any individual's BMI to be converted to a standard deviation score (SDS) thus adjusting for age and sex simultaneously. Measurements of dietary intake, height and weight were available on 1444 children aged 1.5±4.5 y. The body mass index SDS was calculated for each child. Results Some physical characteristics of the 1444 children are shown in Table 1. The boys were signi®cantly taller than the girls (t 2.06, P < 0.05) and signi®cantly heavier (t 4.22, P < 0.01). Both BMI and BMI SDS were signi®cantly greater in the boys than in the girls (t 4.50, P < 0.01) and (t 7.30, P < 0.01) respectively. Table 1 Some characteristics of the children studied Males (n 721) Age (y) Height (m) Weight (kg) BMI (kg/m2) BMI SDS Females (n 723) Mean s.d. Mean s.d. 2.97 0.950 14.87 16.4 0.30 0.82 0.074* 2.59** 1.6*** 1.12**** 2.98 0.942 14.30 16.0 70.14 0.83 0.076 2.49 1.5 1.13 * t 2.06, P < 0.05; ** t 4.22, **** t 7.30, P < 0.01. P < 0.01; *** t 4.50, P < 0.01; Table 2 The mean and standard deviation of energy intake and macronutrient intake in the boys and girls in the survey Males (n 721) Energy intake (kcal/d) Carbohydrate intake (g/d) Energy from carbohydrate (%) Protein intake (g/d) Energy from protein (%) Fat intake (g/d) Energy from fat (%) Females (n 723) Mean s.d. Mean s.d. 1184 162.9 51.6 37.6 12.8 47.0 35.6 258* 40** 6.2 10.3*** 2.6**** 13.1***** 5.3****** 1118 151.5 50.9 36.5 13.1 44.9 36.0 248 37 6.1 10.3 2.5 12.7 5.2 * t 4.92, P < 0.01; ** t 5.60, P < 0.001; *** t 2.06, P < 0.05; **** t 2.27, P < 0.05; ***** t 3.03, P < 0.01; ****** t 2.22, P < 0.05. Table 3 The percentage of children whose BMI SDS was greater than 1.5 within quintiles of macronutrient intakes Fifths of % energy intake from Carbohydrate Protein Fat 1 13.1 11.1 10.4 Boys Girls Percentage of BMI SDS > 1.5 Percentage of BMI SDS > 1.5 2 7.6 10.3 11.0 3 13.1 11.1 11.8 4 11.8 11.8 12.5 5 11.1 12.5 11.1 1 6.3 8.3 11.8 2 6.9 8.3 8.3 3 6.9 9.0 11.1 4 5.6 9.0 6.3 5 9.7 7.6 4.9 445 Diet composition and BMI in pre-school children PSW Davies 446 Table 4 Results of multiple regression analysis with BMI SDS being the dependant variable and percentage energy from protein, fat and carbohydrate being the independent variables Boys Predictor Constant % energy from carbohydrate % energy from protein % energy from fat Girls Coef®cient Standard deviation t-ratio P Coef®cient Standard deviation t-ratio P 78.31 0.081 0.103 0.086 52.30 0.522 0.521 0.524 70.16 0.16 0.20 0.16 0.87 0.87 0.84 0.87 1.56 70.018 0.028 70.031 47.24 0.472 0.470 0.474 0.03 70.04 0.06 70.07 0.97 0.97 0.95 0.95 Figure 1 The mean two standard errors of BMI SDS for the boys within quintiles for macronutrient intake. percentage energy intake from any nutrient group and BMI SDS. Discussions The NDNS of children aged 1.5±4.5 y, although designed speci®cally to be a survey, offers the ability to investigate Figure 2 The mean two standard errors of BMI SDS for the girls within quintiles for macronutrient intake. important nutritional questions because of the size and extent of the data collected. One such question is the extent to which diet composition in¯uences body size in this age group. In this study of 1444 children aged 1.5± 4.5 y we have failed to ®nd a relationship between diet composition and body size as measured by BMI. Diet composition and BMI in pre-school children PSW Davies Diet composition was assessed via a four day weighed intake. While such an approach can be subject to error and bias, previous work in the same age group has shown that estimates of energy intake via a four day weighed intake and measurement of total energy expenditure using doubly labelled water differed by only 37 kcal/d on average (Davies et al, 1994). The four day weighed intake was carried out by the parents (usually the mother) after extensive instruction by a highly trained ®eld worker. The most up to date databases were used to convert food intake into nutrient intakes and hence we are con®dent that the data obtained by this method is of the highest quality. Body size was assessed using BMI. There are other techniques that might assess body composition with greater accuracy than BMI, however many of the techniques do not lend themselves to large scale, community based studies. Nevertheless using the recently published reference values (Cole et al, 1995) for BMI and by adjusting for age and sex simultaneously by the use of SD scores enables the best possible estimate of body size in such large scale studies. The coef®cient of variation of fat, carbohydrate and protein in grams/day was 28%, 25% and 27% respectively in the girls, and 28%, 26% and 25% in the boys, indicating considerable variation in intakes within the cohort. For example, there was almost a three times variation in fat intake between the 5th percentile and 95th percentile value in both sexes. BMI also varied considerably with the cohort, with the coef®cient of variation being 10% and 9% in the boys and girls respectively. Some of this variation will be due to changes in the distribution of BMI with age, however when aged and sex are adjusted for by the use of BMI SDS values the range of such values are from 74.9 to 6.0, again indicating much variation, as would be expected, in the entire cohort. Thus it is unlikely that small ranges in data collected has masked any relationship between BMI and diet composition in this group. It was unknown whether or not the effect of considerable variation in dietary intake would manifest itself as differences in body size in preschool children, indeed that was one of the major aims of the current study. While we have not been able to demonstrate a relationship between diet composition and body size in this group, other smaller studies have found a relationship in older children (Gazzaniga & Burns, 1993; Rolland-Cachera et al, 1995; Oretega et al, 1995) and adults (Dreon et al, 1988; Kromhout et al, 1988; Romieu et al, 1988; Miller et al, 1990; Tucker & Kano, 1992). It is possible that if diet composition does in¯uence body size there is a time course over which the in¯uence takes place and that the group of children studied here (1.5±4.5 y) was too young to reveal such a relationship. This would mean however that there may be a need to target education on good eating habits to parents and carers of younger children in order to prevent the potentially detrimental changes to body habitus occurring in later childhood and adulthood. Other factors such as energy intake per se and lack of habitual activity may have a more important short term effect on BMI of pre-school children. Also, the limitations of a cross-sectional study such as the one reported here should be remembered. Longitudinal studies might reveal that dietary habits in terms of diet composition might predict changes in body mass index and body composition, especially if the relationship does develop over time as previously suggested. There are other techniques that might assess body composition with a greater accuracy than BMI however many of these techniques do not lend themselves to large scale community based studies. However using the recently published reference values for BMI and adjusting for age and sex by the use of SD scores enables the best possible estimate of body size and body composition in such large scale studies. In a large cohort of pre-school children we are unable therefore to con®rm the recent ®ndings (Gazzaniga & Burns, 1993; Rolland-Cachera et al, 1995; Oretega et al, 1995), in much smaller samples of older children, that diet composition effects body size. 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