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British Journal of Developmental Psychology (2014), 32, 78–93 © 2013 The British Psychological Society www.wileyonlinelibrary.com
Children’s and adults’ understanding of the impact of nutrition on biological and psychological processes Lakshmi Raman* Department of Psychology, Oakland University, Michigan, USA Four studies examined children’s and adults’ beliefs about the impact of nutrition on growth and mood states. In Studies 1 and 2, 271 participants (preschoolers through adults) judged the impact of healthy and unhealthy nutrition on height and weight. In Studies 3 and 4, 267 participants judged the impact of healthy and unhealthy nutrition on positive and negative mood states. The results suggest that young children demonstrate a co-existence of an ontologically distinct theory of biology as well as a theory of cross-domain interaction when reasoning about the impact of food on biological and psychological processes.
The study of children’s understanding of biological processes has sparked an ongoing debate as to whether children possess an autonomous theory of biology (Wellman & Gelman, 1992) or whether children demonstrate a cross-domain interaction model (Raman & Gelman, 2008). The autonomous theory of biology states that children as young as 3 years of age consistently apply biological causes for biological processes (Kalish, 1997; Notaro, Gelman, & Zimmerman, 2001). Moreover, they reject non-biological causes for biological processes. Several studies in the domain of children’s biological theories have focused on children’s germ theories such as the understanding of common contagious illness (Kalish, 1996; Raman & Gelman, 2005; Springer & Ruckel, 1992). The results from these studies demonstrated that children as young as 3 years of age recognize that invisible biological entities such as germs (not moral or social factors) cause common contagious illness. However, another area of research that has presented contrary findings to the autonomous theory of biology model is the cross-domain interaction model. This model states that children and adults entertain psychological causes for biological processes and vice versa. Inagaki and Hatano (1993) found that while the majority of Japanese 4- to 6-year-olds reasoned that biological activities would affect the susceptibility to catching a cold, these children also believed that social/psychological factors such as telling a lie or pinching a friend would result in catching an illness. Raman and Gelman (2008) found that preschoolers through second graders reasoned that people were more likely to contract a contagious illness from someone they did not know than someone they knew, suggesting that social relatedness can influence the contraction of an illness. Thus, these two competing theoretical camps disagree as to whether children of different ages maintain strict boundaries between biological and non-biological events. *Correspondence should be addressed to Lakshmi Raman, Department of Psychology, Oakland University, Oakland, MI 48309, USA (email: [email protected]). DOI:10.1111/bjdp.12024
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The following four studies further explore this debate by assessing the impact of nutrition (another subdomain of biology) on biological and psychological processes. This area of research is important as the investigation of the impact of nutrition on growth (a biological factor) and mood states (a psychological factor) will directly address the theoretical debate of whether children demonstrate an autonomous theory of biology and/or a cross-domain interaction model. One of the pressing questions is what makes nutrition a unique biological factor to assess whether children demonstrate an autonomous theory of biology or a cross-domain interaction model? Nutrition is an interesting biological causal factor as it can have both positive and negative biological consequences that can be consciously controlled depending on the kind of food that is eaten. In most cases, healthy nutrition can have a positive biological effect such as contributing to height but reducing weight, whereas unhealthy nutrition can have an impact on increasing weight, but not necessarily on height (the one caveat that must be made clear here is the fact that there is more of a genetic contribution to determining height than there is to weight, but when all other things are held equal, we would predict that an individual who receives healthy nutrition is more likely to grow taller than an individual who receives unhealthy nutrition). Growth is an interesting biological process because it is an involuntary physiological state that is mediated by physical processes. Mood states are psychological states mediated by mental and physical processes and can be either voluntary or involuntary (we have more control on some of our mood states than others). However, few studies have examined American children’s understanding of biological factors such as nutrition on the biological process of growth and psychological processes such as mood states. Wellman and Johnson (1982) examined what children know about a variety of nutritional inputs and the consequences of different diets. Although they found that even kindergartners know that some diets lead to growth and health, whereas other diets lead to weight gain and laziness, kindergartners differed from third and sixth graders in that they thought that consumption of any food would lead to a gain in height and weight. Other studies have examined children’s knowledge about food and the digestive system. Researchers found that young children associate the stomach with food, but they do not have any knowledge about the internal digestive processes until they are about 10 years of age (Gellert, 1962; Teixeira, 2000). Studies also have examined children’s conceptual understanding of what makes food healthy/unhealthy (McKinley et al., 2005). The primary difference was that older children classified food based on nutritional value as opposed to younger children who based their judgements on the taste and enjoyment of the food. Slaughter and Ting (2010) found that between the ages of 5 and 8 years among Australian participants, there were significant increases in mechanistic and vitalistic reasoning about food and nutrition when assessing the purpose of eating, effects of different quantities of food, effects of specific foods, and effects of an unbalanced diet. In a non-Western population, Inagaki (1997a,b) found that Japanese 6-year-olds recognized that nutrition could influence the susceptibility to illness and that 6-year-olds could generate some explanations as to why this was the case. Studies 1 and 2 in this article examined the short-term and long-term role of nutrition on the biological process of height and weight. Studies 3 and 4 examined the effects of short-term and long-term nutrition on positive and negative mood states. The temporal factor was varied across the four studies to determine whether children think that
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timelines of eating healthy and/or unhealthy food will affect growth and/or mood states. The participants in all four studies were primarily European American and were from middle-income homes. The children were residents of a small Midwestern city and neighbouring suburbs. The adults were enrolled in a large public university. Participants who took part in any one study did not participate in any of the other studies.
STUDY 1 The major question of interest is whether children think that healthy and/or unhealthy nutrition has an impact on growth (height and weight). On the basis of previous research (Kalish, 1996; 1997; Raman & Gelman, 2005; Wellman & Johnson, 1982), the prediction is that children would associate nutrition as having an effect on growth, but it is unclear whether they would recognize the differential effects of the impact of healthy versus unhealthy nutrition on growth.
Method Participants Participants in the main study were 30 four- and five-year-olds (13 girls and 17 boys, M age = 4 years 9 months, range = 4 years 2 months–5 years 7 months), 23 six- to eight-year-olds (10 girls and 13 boys, M age = 7 years 6 months, range = 6 years 11 months–8 years 6 months), 27 nine- to ten-year-olds (16 girls and 11 boys, M age = 9 years 6 months, range = 9 years 2 months–10 years 5 months), 27 ten- to twelve-year-olds (17 girls and 10 boys, M age = 11 years 6 months, range = 10 years 6 months–12 years 0 month), and 29 adults (23 women and 6 men, M age = 19 years 5 months, range = 18 years 2 months–53 years 7 months).
Materials Pre-test Prior to this study, a separate group of adults (n = 30) was asked to create an open-ended list of what they thought were healthy and unhealthy foods. The items that were most frequently listed across several food groups were selected as being representative of healthy and unhealthy foods. These foods were then presented to a separate group of preschoolers (n = 30), and they were asked to let the experimenter know whether they thought the foods were good for them to eat (all the preschoolers were familiar with all the healthy and unhealthy food items, and they clearly understood what it meant when they were asked whether an item was good for them to eat). The preschoolers’ responses were not significantly different from adult responses, ps > .05, demonstrating that preschoolers’ ideas about which foods were healthy or unhealthy were not significantly different from adults.
Main task The main task presented each participant with two conditions: height and weight. Within each condition, each participant was presented with 12 vignettes in each condition (6 vignettes describing characters who consumed healthy foods and 6 characters who consumed unhealthy foods; Table 1).
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Table 1. Selection of healthy and unhealthy foods presented for Studies 1–4 Healthy foods
Unhealthy foods
Broccoli Grapes Peas Apples Cereal Oatmeal
Hash browns Pizza Donuts Fried chicken French fries Hamburgers
The questions for all the healthy and unhealthy foods were identical except for the foods that were listed in each of the vignettes. Prior to the main vignettes, children were presented with two control questions with items that were unrelated to height and weight to ensure that they were familiar with the term ‘they will both grow the same’. An example of one of the vignettes for the healthy foods for height was the following: there are two boys, Brian and Nick. Brian eats all of his broccoli for dinner. Nick does not eat any of his broccoli for dinner. Who do you think is going to grow taller? (1) Brian, (2) Nick, (3) or will they both grow the same. Identical vignettes were used for the weight questions with the exception that children were asked ‘Who is going to become fatter?’ (The term ‘fatter’ was used as the youngest children in this study were familiar with this term. Pilot testing revealed that the youngest children were not familiar with other terms such as ‘heavier’ or ‘gaining weight’.)
Procedure Children were interviewed individually. They were shown hand-drawn black-and-white stick figures of the two characters in each question. The purpose of using pictures was to hold the child’s attention; the pictures did not make any reference to the height or weight of the two characters in question, and the same pictures were used for all the vignettes in both conditions. The experimenter read the vignettes to the child, pointing to the relevant card when reading the particular item. Participants were asked to answer each vignette, and their response was noted. Across all studies, the presentation of the character who ate the food and the character who did not eat the food in the response options was counterbalanced across participants within each age group so that half of the participants got the participant who ate the food first and the other half got the character who did not eat the food first. To minimize confusion for the youngest age group, the option ‘or they will both grow the same’ was always presented as the third option. For each participant, items were randomized within each condition. Adults received a testing booklet that contained the two conditions and the 12 vignettes in each condition (with no pictures) and were asked to write down their responses in the booklets.
Statistical analyses A score of 1 was assigned if participants responded that the person who ate the food would grow tall or fat, 0 was assigned if participants responded that the person who did not eat the food would grow tall or fat, and 0.5 was assigned if ‘they will grow the same’ response is selected.
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Findings from the analyses of variance A 5 (age group) 9 2 (food type) 9 2 (condition) analysis of variance (ANOVA) focusing on whether eating healthy and unhealthy food would affect height and weight was conducted. The results indicated a significant food 9 age group interaction, F(4, 131) = 2.77, p < .03, a significant condition 9 food interaction, F(1, 131) = 178.64, p < .01, and a significant condition 9 food 9 grade interaction, F(4, 131) = 22.14, p < .01. There was also a significant grade difference, F(4, 131) = 6.69, p < .01. Post-hoc Bonferroni tests indicated that overall participants recognized that healthy foods would promote a gain in height, ps < .01, whereas unhealthy foods would result in weight gain, p < .01. Post-hoc Bonferroni tests were also conducted to isolate the sources of the condition effect in the 3-way interaction. Second graders recognized that healthy foods are more likely to result in height gain, p < .05, but they did not differentiate that eating unhealthy foods would result in weight gain, p > .73. Instead, similar to preschoolers, they reasoned that eating unhealthy foods would result in an increase in both height and weight. It was only at fourth grade and older that participants consistently recognized that healthy eating would result in an increase in height, whereas unhealthy eating would result in an increase in weight, ps < .01 (see Figure 1a,b for mean growth responses across condition and grade). The results of these analyses suggest that it is only at fourth grade that children obtain a completely differentiated understanding of the impact of healthy and unhealthy nutrition on growth.
Discussion This study examined children’s recognition of the impact of healthy and unhealthy nutrition on height and weight. The most interesting part of the study was the developmental difference obtained between the younger and the older children. Preschoolers reasoned that the consumption of both healthy and unhealthy foods would result in both growing taller and fatter, similar to what Au and Romo (1999) have termed as the input–output concept where the input is food and the output is growth. However, second graders reasoned that healthy foods are more likely to promote an increase in height, but they reasoned that both healthy and unhealthy foods would result in an increase in weight. It was only at the fourth and older grades that there was evidence of a differentiation of the effects of healthy and unhealthy nutrition on height and weight. The results with younger children suggest that they demonstrate a global ontological domain in the realm of biology when assessing the impact of food on the biological process of growth (Kalish, 1997; Raman & Gelman, 2005; Wellman & Johnson, 1982). The question that these results raise is why is it that although children are receiving a plethora of information about healthy eating from the environment (Jacobson & Maxwell, 1994), they fail to differentiate between the effects of healthy and unhealthy foods on growth? First, one possible reason for this early lack of differentiation might be that the vignettes stated that one of the characters ate the food, whereas the other character did not. Thus, young children may be interpreting the vignettes to mean that the characters either ate or did not eat a food for a single meal which may not have a differentiated effect on growth which is a perfectly reasonable conclusion. However, the older children seem to infer that eating a healthy food even for one meal implies that the
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(a)
(b)
Figure 1. (a) Mean number of tall responses across grades for the consumption of healthy and unhealthy foods for Study 1. (b) Mean number of fat responses across grades for the consumption of healthy and unhealthy foods for Study 1.
person is possibly a healthy eater in general, thus affecting biological processes such as height and weight. Study 2 addresses this limitation by clearly stating the timeline of the food consumption. Second, older children may have more of an understanding of the underlying nutritional impact of the food. If this is the case, the results of Study 2 should replicate those of Study 1.
STUDY 2 In Study 2, participants were presented with identical vignettes as in Study 1, but this time the temporal timeline of the food being consumed/not consumed was clearly stated.
Method Participants The sample included 26 four- and five-year-olds (15 girls and 11 boys, M age = 4 years 5 months, range = 4 years 2 months–5 years 1 month), 26 seven- and eight-year-olds
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(10 girls and 16 boys, M age = 7 years 4 months, range = 7 years 0 month–8 years 5 months), 27 nine- and ten-year-olds (13 girls and 14 boys, M age = 9 years 4 months, range = 9 years 2 months–10 years 7 months), 25 ten- and twelve-year-olds (16 girls and 9 boys, M age = 11 years 7 months, range = 10 years 11 months–12 years 2 months), and 29 adults (22 women and 7 men, M age = 20 years 4 months, range = 18 years 2 months–48 years 0 month).
Materials The materials were identical to that of Study 1. The only difference was that the vignettes clearly stated that the characters did or did not eat food everyday (e.g., Brian eats (does not eat) all of his broccoli for dinner every day).
Procedure The procedure and coding were identical to those of Study 1.
Results from the analysis of variance A 5 (age group) 9 2 (food type) 9 2 (condition) analysis of variance (ANOVA) focusing on whether eating healthy and unhealthy food would affect height and weight was conducted. The results indicated a significant food 9 age group interaction, F(4, 128) = 3.92, p < .01, a significant condition 9 food interaction, F (1, 128) = 220.38, p < .01, and a significant condition 9 food 9 grade interaction, F (4, 128) = 37.41, p < .01. There was also a significant grade difference, F(4, 128) = 3.04, p < .02. Overall participants recognized that healthy foods would results in an increase in height, ps < .01, whereas unhealthy foods would result in an increase in weight, ps < .01. Post-hoc Bonferroni tests indicated that it was only at fourth grade and higher that children differentially recognized that healthy foods would promote a gain in height, ps < .01, whereas unhealthy foods would result in a gain in weight, ps < .01 (see Table 2 for mean growth responses across condition and grade). These results replicate the results of Study 1 because it is only at fourth grade that children consistently recognize the differential effect.
Table 2. Mean number of ‘tall’ and ‘fat’ responses (out of a maximum of 6) for each grade across conditions for Study 2 Tall Grade Preschool Second Fourth Sixth College
Fat
Healthy
Unhealthy
Healthy
Unhealthy
4.1 (1.45) 5.2 (1.48) 5.0 (1.34) 5.3 (0.86) 4.6 (1.1)
4.1 (1.15) 4.5 (1.89) 3.0 (1.92) 2.0 (1.47) 3.1 (1.31)
4.1 (1.57) 4.5 (2.19) 2.4 (1.71) 2.4 (1.57) 2.2 (1.57)
4.4 (1.23) 4.6 (1.63) 4.8 (1.38) 5.0 (1.0) 4.6 (1.44)
Note. Numbers in parenthesis indicate standard deviations.
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Discussion The results of this study replicated the results of Study 1. The most important finding is that the younger children judged that any kind of food consumption would result in growing taller and fatter. It was only at fourth grade that children consistently demonstrated a differential impact of eating healthy and unhealthy foods on height and weight. These results support the notion that children’s theory of biology undergoes a developmental shift in middle childhood. As stated earlier, one could argue that the concept of height in particular is not strongly food related but is determined by genetics (unless there are extreme conditions such as a severe lack of food) and that nutrition does not seriously impact height. However, considering that all other factors are equal, it is interesting that we observe a developmental difference in children’s reasoning about the nutritional effects of food on height and weight in middle childhood. These results raise the question as whether young children would still display an autonomous theory of biology when they have to reason about the impact of nutrition on non-biological factors such as psychological factors. Studies 3 and 4 examined whether children and adults think that healthy and/or unhealthy foods can impact the psychological domain of positive and negative mood states.
STUDY 3 The results of the first two studies lead to the question as to whether children and adults would entertain an autonomous theory of biology when reasoning about the impact of nutrition on mood states. One possibility is that even young children will keep the biological and psychological domains distinct arguing that food does not influence mood states. This position would be consistent with the distinct ontological domains theory (Gelman & Wellman, 1991; Notaro et al., 2001; Opfer, 2002). The second possibility is that there will be evidence of the domain interaction model (Nemeroff, 1995; Raman & Gelman, 2008) where children could (1) make an undifferentiated association of food with mood states or (2) show a differentiated recognition of the effects of healthy and unhealthy foods on positive and negative mood states. To test this hypotheses, Study 3 examined the effect of eating healthy and unhealthy foods on positive and negative mood states. As in Study 1, no explicit timeline for food consumption was stated in the vignettes.
Method Participants Participants in the main study were 26 four- and five-year-olds (12 girls and 14 boys, M age = 4 years 9 months, range = 4 years 5 months–5 years 4 months), 22 seven- and nine-year-olds (14 girls and 8 boys, M age = 7 years 5 months, range = 7 years 6 months–9 years 2 months), 28 nine- and ten-year-olds (13 girls and 15 boys, M age = 9 years 5 months, range = 9 years 3 months–10 years 3 months), 27 ten- and twelve-year-olds (13 girls and 14 boys, M age = 11 years 5 months, range = 10 years 11 months–12 years 6 months), and 30 adults (22 women and 8 men, M age = 19 years 6 months, range = 18 years 3 months–22 years 1 month).
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Materials The main task presented each participant with two conditions: positive mood states and negative mood states. Within each condition, each participant was presented with six vignettes describing characters who consumed the same foods as in Studies 1 and 2 (Table 3). A variety of mood states were presented because the objective of the study was to determine whether participants thought that food had an impact on mood states in general. The rationale for selecting these mood states is that it has been shown that even young children are familiar with these positive and negative mood states (Kalish, 1997; Raman & Gelman, 2004). The questions for all the healthy and unhealthy foods were identical except for the foods that were listed in each of the vignettes. An example of one of the vignettes for the healthy foods for the positive mood state was the following: There are two boys, Brian and Nick. Brian eats all of his broccoli for dinner. Nick does not eat any of his broccoli for dinner. Who do you think is going to feel more satisfied? (1) Brian; (2) Nick; (3) or will they both feel the same.
The vignette for the negative mood state was identical except that a negative mood was presented in the vignette.
Procedure and coding The procedure and coding was identical to that of Studies 1 and 2.
Results from the analysis of variance Recall that the primary interest was in determining whether children think that food can influence mood states. A 5 (age group) 9 2 (food type) 9 2 (condition) analysis of variance (ANOVA) focusing on whether eating healthy and unhealthy food would affect positive and negative mood states was conducted. The results indicated a significant main effect for mood, F(1, 128) = 459.66, p < .01, a significant condition 9 grade interaction, Table 3. (a) Positive mood states and (b) negative mood states that were paired with healthy and unhealthy foods for Studies 3 and 4
Positive mood states Satisfied Happy Excited Friendly Calm Delighted Negative mood states Sorry Guilty Angry Sad Cranky Frustrated
Healthy foods
Unhealthy foods
Broccoli Grapes Peas Apples Cereal Oatmeal
Hamburger Pizza French Fries Hash browns Donuts Fried chicken
Broccoli Grapes Peas Apples Cereal Oatmeal
Hamburger Pizza French Fries Hash browns Donuts Fried chicken
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(a)
(b)
Figure 2. (a) Mean number of responses across grades for healthy and unhealthy foods for the positive mood condition for Study 3. (b) Mean number of responses across grades for healthy and unhealthy foods for the negative mood condition for Study 3.
F(4, 128) = 21.63, p < .01, a significant condition 9 food interaction, F(1, 128) = 31.58, p < .01, and a significant condition 9 food 9 grade interaction, F(4, 128) = 2.83, p < .05. There was also a significant grade difference, F(4, 128) = 16.35, p < .01. Overall participants generated higher scores for positive mood states compared with negative mood states, ps < .01. Preschoolers associate eating healthy food with positive mood states compared with negative mood states, p < .01, but they reasoned that unhealthy food would have an effect on both positive and negative mood states, ps > .05. All other grades associated eating healthy foods with positive mood states and unhealthy foods with negative mood states, ps < .01 (Figure 2a,b).
Discussion Study 3 examined children’s and adults’ judgements about the effects of eating healthy and unhealthy foods on positive and negative mood states. In this study, even preschoolers associated eating healthy foods with positive mood states, but similar to the preschoolers in Studies 1 and 2, they judged that eating unhealthy food would have an
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impact on both positive and negative mood states. This indicates that children seem to display an earlier sensitivity to the impact of food on mood states than about the impact of food on the biological process of growth. Taken together, these results support the notion that young children entertain a cross-domain interaction model when assessing the impact of nutrition on mood states. Interestingly, young children associated eating healthy but generally distasteful foods such as broccoli as contributing to positive mood states, suggesting that they did not let their taste bias affect their judgements. The results of this study raise an interesting question as to whether children and adults would show similar patterns if they were asked what the effects of eating these foods were on a long-term daily basis. This scenario was explored in Study 4.
STUDY 4 Study 4 explores whether the long-term consumption of healthy and unhealthy foods would have an impact on mood states. There are two possible outcomes. First, older children might show similar patterns to Study 3 by associating eating healthy foods and unhealthy foods on a long-term basis with positive moods states and negative mood states, respectively. The second pattern that might emerge is that children might judge that food eaten on a long-term basis may erase some of the short-term pleasure or even create negative physical and psychological consequences.
Method Participants The sample included 24 four- and five-year-olds (11 girls and 13 boys, M age = 4 years 6 months, range = 4 years 0 month–5 years 10 month), 29 six- to nine-year-olds (13 girls and 16 boys, M age = 7 years 5 months, range = 6 years 4 months–9 years 0 month), 23 nine- and ten-year-olds (14 girls and 9 boys, M age = 9 years 7 months, range = 9 years 3 months–10 years 8 months), 31 eleven- and twelve-year-olds (11 girls and 20 boys, M age = 11 years 6 months, range = 11 years 4 months–12 years 8 months), and 27 adults (19 women and 8 men, M age = 22 years 6 months, range = 18 years 4 months– 54 years 8 months).
Materials Participants received identical vignettes as in Study 3. The one difference was that the character in each of the vignettes ate the food on a daily basis and the other character did not eat the food on a daily basis.
Procedure The procedure and the coding was identical to that of Studies 1, 2, and 3.
Results from the analysis of variance Recall that the primary interest was in determining whether children think that eating healthy/unhealthy foods on a long-term basis can influence mood states. A 5 (age
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Table 4. Mean number of ‘positive’ and ‘negative’ responses (out of a maximum of 6) for each grade across conditions for Study 4 Positive Grade Preschool Second Fourth Sixth College
Negative
Healthy
Unhealthy
Healthy
Unhealthy
2.3 (1.0) 4.8 (.91) 5.3 (0.94) 5.3 (.79) 5.0 (.77)
2.4 (0.99) 4.7 (1.0) 4.2 (1.33) 4.4 (1.25) 3.7 (1.56)
2.0 (1.41) 0.8 (0.95) 0.4 (.65) 0.6 (.88) 1.1 (1.59)
1.9 (1.17) 1.2 (1.17) 2.1 (1.54) 1.4 (1.12) 2.9 (.159)
Note. Numbers in parenthesis indicate standard deviations.
group) 9 2 (food type) 9 2 (condition) analysis of variance (ANOVA) focusing on whether eating healthy and unhealthy food would affect positive and negative mood states was conducted. The results indicated a significant main effect for mood, F(1, 129) = 527.17, p < .01, a significant condition 9 grade interaction, F(4, 129) = 26.34, p < .01, a significant condition 9 food interaction, F(1, 129) = 54.92, p < .01, and a significant condition 9 food 9 grade interaction, F(4, 129) = 8.61, p < .05. There was also a significant grade difference, F(4, 129) = 14.4, p < .01. Post-hoc Bonferroni tests revealed that overall participants generated higher means for positive mood states than for negative mood states, p < .01. Across participants, eating healthy food was associated with positive mood states and eating unhealthy food was associated with negative mood states, ps < .01. However, preschoolers did not discriminate that eating healthy foods on a long-term basis would result in positive mood states and eating unhealthy food would result in negative mood states; they reasoned that food would overall contribute to mood states, ps > .24. It was only at second grade and higher that children consistently associated eating healthy foods with positive mood states and unhealthy foods with negative mood states (see Table 4 for mean responses across grade for healthy and unhealthy foods for positive and negative mood states).
Discussion The primary purpose of Study 4 was to determine whether participants thought that eating a food on a long-term basis might have an effect on positive and/or negative mood states. The results closely replicated the results of Study 3 with the exception that preschoolers judged that when a food is consumed on a long-term basis, it will not have a differential effect on mood states. Although justifications were not asked for in these studies, some preschoolers spontaneously explained that eating something on a daily basis would not be responsible for how a person feels, but food in general (irrespective of whether it was healthy or unhealthy on a long-term basis) is likely to make a person feel good. Thus, the results of this study clearly indicate that children clearly seem to entertain a cross-domain interaction model when associating the effects of food on mood states.
GENERAL DISCUSSION Four studies examined whether children and adults demonstrated an ontologically distinct model of biology or a cross-domain interaction model when assessing the impact
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of healthy and unhealthy foods on the biological process of growth and psychological process of mood states. The results indicated that preschoolers demonstrate an ontologically distinct but undifferentiated model of biology when assessing the impact of food on growth. However, there is a developmental shift in fourth grade when children make a differential attribution of the impact of food on growth. In Study 3, preschoolers associated eating healthy foods with positive mood states, whereas they thought that eating unhealthy foods would contribute to both positive and negative mood states. In Study 4, it was only at second grade and older that children associated eating healthy foods on a long-term basis with positive mood states and unhealthy foods with negative mood states. Contrary to the work by Scott-King and Nemeroff (1989) where they found that children grow into the idea of ‘you are what you eat’ (implying that the food you ingest will result in you taking on the physical and psychological properties of that food), these results demonstrate that even young children associate the ingestion of food as having an impact on mood states. These findings suggest that young children may have a more differentiated development of a cross-domain interaction model. This might seem surprising in the light of previous research showing that children treat the biological and psychological domains as wholly distinct (Notaro, 2001). Although most studies have examined the impact of psychological factors on biological processes (Inagaki & Hatano, 1993; Notaro, Gelman, & Zimmerman, 2002) based on previous research, children would be expected to keep the two domains somewhat distinct. One possible explanation is that children demonstrate a co-existence of a theory of biology as well as a cross-domain interaction model. For example, Raman and Gelman (2008) found that young children entertain psychogenic factors as having an impact on the possibility of contracting an illness. Heyman, Phillips, and Gelman (2003) found that 5-year-olds showed systematic tendencies to take animacy into account when making predictions about principles of physics (predicting that the path an item takes when it falls will differ, depending on whether it is animate or inanimate). These findings are analogous to the findings reported in Studies 3 and 4. A second possibility is that children think that the effect of food on mood states is more immediate than the effect food has on biological processes such as growth. For example, if you eat something, you are more likely to feel satisfied or disgusted in a relatively short period of time (as opposed to eating something and growing tall or putting on weight). Thus, they might find it easier to infer that food can impact psychological mood states. The present results corroborate the suggestion that young children have a distinct ontological domains approach by the early preschool years. Preschoolers and second graders in Studies 1 and 2 did recognize that the consumption of food will result in a gain in height and weight, arguing for the notion that young children recognize that biological factors have an impact on biological processes. However, young children’s theory of biology was based on an input–output concept compared with older children, as they did not distinguish the differential effects of eating healthy and unhealthy foods on height and weight. Studies 3 and 4 presented notable findings in that even young children demonstrated a domain interaction. This is not an unreasonable association (as shown by results from other adult studies mentioned earlier) because what we eat can have physiological or psychological consequences that affect our mood states. The most pressing question is why young children seem to apply an input–output relationship when reasoning about the differential effects of eating healthy and unhealthy foods on height and weight, whereas with other biological processes such as illness, they seem to demonstrate more sophisticated reasoning even in the preschool years (Raman & Gelman, 2005). There are two possible arguments. First, children may be using a global
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input–output relationship when reasoning about the differential impact of food. Second, children might have varied developmental levels in their recognition of different biological processes (similar to Piaget’s notion of horizontal decalage). Thus, they might develop a more differentiated recognition of the mechanisms involved in illness at an earlier age than the mechanisms involved in growth. This would argue for the notion that their theory of biology is one that develops over several years starting in early childhood and well into adulthood as shown by several studies in which even adults do not show a differentiated response when reasoning about biological processes (Au & Romo, 1999; Raman & Winer, 2004). A third argument would be that the impact of food does not present a direct cause and effect relationship. Several other factors such as genetics play a major role in determining the height and weight of an individual which in turn might make differentiated reasoning about the effects of food more difficult for younger children. One difficult and unresolved question is whether one can predict in more systematic ways when children and even adults will predict that domains will interact (as in the present studies) and when children will inappropriately predict that domains will not interact (as in the Notaro et al., 2001). Both types of reasoning (although seemingly opposite) result from the same source – young children are trying to learn the extent of domain boundaries and what implications they have for reasoning. The world is complex and sometimes both domains do interact, for example one’s mood can be affected by what one eats. Interestingly, domain interaction reasoning never seems to disappear over age (as evidenced by the fact that adults also reliably associated eating healthy foods with positive mood states and unhealthy foods with negative mood states). There are some limitations to these studies. First, some might argue that the foods that are presented as healthy and unhealthy are not all truly healthy or unhealthy (e.g., fried chicken has high levels of fat but also high levels of protein; cereal is generally viewed as nutritious, but most cereals have a high amount of sugar in them). However, overall, the healthy foods presented in these studies are low in fats and sugars, whereas the unhealthy foods are high in fat. Although this distinction is not absolute, it is still a distinction that children recognize (as demonstrated with the pre-test prior to running Study 1). Second, it can be argued that the foods presented are somewhat limited in number and do not represent a large variety of healthy/unhealthy foods. The reason for this is that the number of items had to be small so that the task would not be too cognitively demanding for preschoolers. Overall, the results of these studies demonstrate that children and adults entertain a co-existence of an ontologically distinct theory of biology as well as a cross-domain interaction model when assessing the impact of nutrition on growth and mood states. These results are a first step in demonstrating the important developmental changes that are taking place between preschool and middle childhood in how children come to understand and sort out the impact of biological factors on biological and psychological processes.
Acknowledgements Preparation of this article was supported by a grant from the National Institute of Child Health and Human Development 1 R15 HD058303-01A1 to Raman. Portions of this research were presented at the 2009 Cognitive Development Society conference in San Antonio, Texas. I would like to thank the parents, children, and teachers in the Oxford School district for their participation. I also thank Jennifer Kelley and Alessa Petersen for their assistance in data
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collection. I am grateful to Todd Shackelford for his constructive comments and feedback on a draft of the manuscript.
References Au, T. K., & Romo, L. (1999). Mechanical causality in children’s folkbiology. In D. L. Medin & S. Atran (Eds.), Folkbiology (pp. 355–391). Cambridge, MA: MIT Press. Gellert, E. (1962). Children’s conceptions of the content and function of the human body. Genetic Psychology Monographs, 65, 293–305. Gelman, S. A., & Wellman, H. M. (1991). Insides and essences: Early understanding of the non-obvious. Cognition, 38, 214–244. Heyman, G. D., Phillips, A. T., & Gelman, S. A. (2003). Children’s reasoning about physics within and across ontological kinds. Cognition, 89, 43–61. doi:10.1016/S0010-0277(03)00072-6 Inagaki, K. (1997a, April). Endogenous variables mediating disease transmission. Washington, DC: Paper presented at the meeting for the Society of Research in Child Development. Inagaki, K. (1997b). Emerging distinction between na€ıve biology and na€ıve psychology. In H. M. Wellman & K. Inagaki (Eds.), The emergence of core domains of thought: Children’s reasoning about physical, psychological, and biological phenomena (pp. 27–44). San Francisco, CA: Jossey-Bass. Inagaki, K., & Hatano, G. (1993). Young children’s understanding of the mind-body distinction. Child Development, 64, 1534–1549. doi:10.2307/1131551 Jacobson, M. F., & Maxwell, B. (1994). What are we feeding our kids?. New York, NY: Workman. Kalish, C. W. (1996). Causes and symptoms in preschoolers’ conceptions of illness. Child Development, 67, 1647–1670. doi:10.2307/1131723 Kalish, C. W. (1997). Preschoolers’ understanding to mental and bodily reactions to contamination. What you don’t know can hurt you, but cannot sadden you. Developmental Psychology, 33, 79– 91. doi:10.1037//0012-1649.33.1.79 McKinley, M. C., Lowis, C., Robson, P. J., Wallance, J. M. W., Morrisey, M., Moran, A., & Livingstone, M. B. E. (2005). It is good to talk: Children’s view on food and nutrition. European Journal of Clinical Nutrition, 59, 542–551. doi:10.1038/sj.ejcn.1602113 Nemeroff, C. J. (1995). Magical thinking about illness virulence: Conception of germs from “safe” versus “dangerous” others. Health Psychology, 14, 147–151. doi:10.1037//0278-6133.14.2.147 Notaro, P. C., Gelman, S. A., & Zimmerman, M. A. (2001). Children’s understanding of psychogenic bodily reactions. Child Development, 72, 444–459. doi:10.1111/1467-8624.00289 Notaro, P. C., Gelman, S. A., & Zimmerman, M. A. (2002). Biases in reasoning about the consequences of psychogenic bodily reactions: Domain boundaries in cognitive development. Merrill-Palmer Quarterly, 48, 427–449. doi:10.1353/mpq.2002.0020 Opfer, J. E. (2002). Identifying living and sentient kinds from dynamic information: The case of goal-directed versus aimless autonomous movement in conceptual change. Cognition, 86, 97– 122. doi:10.1016/S0010-0277(02)00171-3 Raman, L., & Gelman, S. A. (2004). A cross-cultural analysis of children’s and adults’ understanding of illness in South Asia and the United States. Journal of Cognition and Culture, 4, 293–317. doi:10.1163/1568537041725088 Raman, L., & Gelman, S. A. (2005). Children’s understanding of the transmission of genetic disorders and contagious illnesses. Developmental Psychology, 41, 171–182. doi:10.1037/0012-1649.41. 1.171 Raman, L., & Gelman, S. A. (2008). Do children endorse psychosocial factors in the transmission of illness and disgust? Developmental Psychology, 44, 801–813. doi:10.1037/0012-1649.44.3.801 Raman, L., & Winer, G. A. (2004). Evidence of more immanent justice reasoning in adults than children: A challenge to traditional developmental theories. British Journal of Developmental Psychology, 22, 255–274.
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Scott-King, K., & Nemeroff, C. (1989). Developmental aspects of magical cognitions about food. Unpublished dataset. Slaughter, V., & Ting, C. (2010). Development of ideas about food and nutrition from preschool to university. Appetite, 55, 556–564. doi:10.1016/j.appet.2010.09.004 Springer, K., & Ruckel, J. (1992). Early beliefs about the causes of illness: Evidence against immanent justice. Cognitive Development, 7, 429–443. doi:10.1016/0885-2014(92)80002-W Teixeira, F. M. (2000). What happens to the food we eat? Children’s conceptions of the structure and function of the digestive system. International Journal of Science Education, 22, 507–520. doi:10.1080/095006900289750 Wellman, H. M., & Gelman, S. A. (1992). Cognitive development: Foundational theories of core domains. Annual Review of Psychology, 43, 337–375. doi:10.1146/annurev.psych.43.1.337 Wellman, H. M., & Johnson, C. N. (1982). Children’s understanding of food and its functions: A preliminary study of the development of concepts of nutrition. Journal of Applied Developmental Psychology, 3, 135–148. doi:10.1016/0193-3973(82)90024-7 Received 13 February 2013; revised version received 2 September 2013
British Journal of Developmental Psychology (2014), 32, 78–93 © 2013 The British Psychological Society www.wileyonlinelibrary.com
Children’s and adults’ understanding of the impact of nutrition on biological and psychological processes Lakshmi Raman* Department of Psychology, Oakland University, Michigan, USA Four studies examined children’s and adults’ beliefs about the impact of nutrition on growth and mood states. In Studies 1 and 2, 271 participants (preschoolers through adults) judged the impact of healthy and unhealthy nutrition on height and weight. In Studies 3 and 4, 267 participants judged the impact of healthy and unhealthy nutrition on positive and negative mood states. The results suggest that young children demonstrate a co-existence of an ontologically distinct theory of biology as well as a theory of cross-domain interaction when reasoning about the impact of food on biological and psychological processes.
The study of children’s understanding of biological processes has sparked an ongoing debate as to whether children possess an autonomous theory of biology (Wellman & Gelman, 1992) or whether children demonstrate a cross-domain interaction model (Raman & Gelman, 2008). The autonomous theory of biology states that children as young as 3 years of age consistently apply biological causes for biological processes (Kalish, 1997; Notaro, Gelman, & Zimmerman, 2001). Moreover, they reject non-biological causes for biological processes. Several studies in the domain of children’s biological theories have focused on children’s germ theories such as the understanding of common contagious illness (Kalish, 1996; Raman & Gelman, 2005; Springer & Ruckel, 1992). The results from these studies demonstrated that children as young as 3 years of age recognize that invisible biological entities such as germs (not moral or social factors) cause common contagious illness. However, another area of research that has presented contrary findings to the autonomous theory of biology model is the cross-domain interaction model. This model states that children and adults entertain psychological causes for biological processes and vice versa. Inagaki and Hatano (1993) found that while the majority of Japanese 4- to 6-year-olds reasoned that biological activities would affect the susceptibility to catching a cold, these children also believed that social/psychological factors such as telling a lie or pinching a friend would result in catching an illness. Raman and Gelman (2008) found that preschoolers through second graders reasoned that people were more likely to contract a contagious illness from someone they did not know than someone they knew, suggesting that social relatedness can influence the contraction of an illness. Thus, these two competing theoretical camps disagree as to whether children of different ages maintain strict boundaries between biological and non-biological events. *Correspondence should be addressed to Lakshmi Raman, Department of Psychology, Oakland University, Oakland, MI 48309, USA (email: [email protected]). DOI:10.1111/bjdp.12024
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The following four studies further explore this debate by assessing the impact of nutrition (another subdomain of biology) on biological and psychological processes. This area of research is important as the investigation of the impact of nutrition on growth (a biological factor) and mood states (a psychological factor) will directly address the theoretical debate of whether children demonstrate an autonomous theory of biology and/or a cross-domain interaction model. One of the pressing questions is what makes nutrition a unique biological factor to assess whether children demonstrate an autonomous theory of biology or a cross-domain interaction model? Nutrition is an interesting biological causal factor as it can have both positive and negative biological consequences that can be consciously controlled depending on the kind of food that is eaten. In most cases, healthy nutrition can have a positive biological effect such as contributing to height but reducing weight, whereas unhealthy nutrition can have an impact on increasing weight, but not necessarily on height (the one caveat that must be made clear here is the fact that there is more of a genetic contribution to determining height than there is to weight, but when all other things are held equal, we would predict that an individual who receives healthy nutrition is more likely to grow taller than an individual who receives unhealthy nutrition). Growth is an interesting biological process because it is an involuntary physiological state that is mediated by physical processes. Mood states are psychological states mediated by mental and physical processes and can be either voluntary or involuntary (we have more control on some of our mood states than others). However, few studies have examined American children’s understanding of biological factors such as nutrition on the biological process of growth and psychological processes such as mood states. Wellman and Johnson (1982) examined what children know about a variety of nutritional inputs and the consequences of different diets. Although they found that even kindergartners know that some diets lead to growth and health, whereas other diets lead to weight gain and laziness, kindergartners differed from third and sixth graders in that they thought that consumption of any food would lead to a gain in height and weight. Other studies have examined children’s knowledge about food and the digestive system. Researchers found that young children associate the stomach with food, but they do not have any knowledge about the internal digestive processes until they are about 10 years of age (Gellert, 1962; Teixeira, 2000). Studies also have examined children’s conceptual understanding of what makes food healthy/unhealthy (McKinley et al., 2005). The primary difference was that older children classified food based on nutritional value as opposed to younger children who based their judgements on the taste and enjoyment of the food. Slaughter and Ting (2010) found that between the ages of 5 and 8 years among Australian participants, there were significant increases in mechanistic and vitalistic reasoning about food and nutrition when assessing the purpose of eating, effects of different quantities of food, effects of specific foods, and effects of an unbalanced diet. In a non-Western population, Inagaki (1997a,b) found that Japanese 6-year-olds recognized that nutrition could influence the susceptibility to illness and that 6-year-olds could generate some explanations as to why this was the case. Studies 1 and 2 in this article examined the short-term and long-term role of nutrition on the biological process of height and weight. Studies 3 and 4 examined the effects of short-term and long-term nutrition on positive and negative mood states. The temporal factor was varied across the four studies to determine whether children think that
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timelines of eating healthy and/or unhealthy food will affect growth and/or mood states. The participants in all four studies were primarily European American and were from middle-income homes. The children were residents of a small Midwestern city and neighbouring suburbs. The adults were enrolled in a large public university. Participants who took part in any one study did not participate in any of the other studies.
STUDY 1 The major question of interest is whether children think that healthy and/or unhealthy nutrition has an impact on growth (height and weight). On the basis of previous research (Kalish, 1996; 1997; Raman & Gelman, 2005; Wellman & Johnson, 1982), the prediction is that children would associate nutrition as having an effect on growth, but it is unclear whether they would recognize the differential effects of the impact of healthy versus unhealthy nutrition on growth.
Method Participants Participants in the main study were 30 four- and five-year-olds (13 girls and 17 boys, M age = 4 years 9 months, range = 4 years 2 months–5 years 7 months), 23 six- to eight-year-olds (10 girls and 13 boys, M age = 7 years 6 months, range = 6 years 11 months–8 years 6 months), 27 nine- to ten-year-olds (16 girls and 11 boys, M age = 9 years 6 months, range = 9 years 2 months–10 years 5 months), 27 ten- to twelve-year-olds (17 girls and 10 boys, M age = 11 years 6 months, range = 10 years 6 months–12 years 0 month), and 29 adults (23 women and 6 men, M age = 19 years 5 months, range = 18 years 2 months–53 years 7 months).
Materials Pre-test Prior to this study, a separate group of adults (n = 30) was asked to create an open-ended list of what they thought were healthy and unhealthy foods. The items that were most frequently listed across several food groups were selected as being representative of healthy and unhealthy foods. These foods were then presented to a separate group of preschoolers (n = 30), and they were asked to let the experimenter know whether they thought the foods were good for them to eat (all the preschoolers were familiar with all the healthy and unhealthy food items, and they clearly understood what it meant when they were asked whether an item was good for them to eat). The preschoolers’ responses were not significantly different from adult responses, ps > .05, demonstrating that preschoolers’ ideas about which foods were healthy or unhealthy were not significantly different from adults.
Main task The main task presented each participant with two conditions: height and weight. Within each condition, each participant was presented with 12 vignettes in each condition (6 vignettes describing characters who consumed healthy foods and 6 characters who consumed unhealthy foods; Table 1).
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Table 1. Selection of healthy and unhealthy foods presented for Studies 1–4 Healthy foods
Unhealthy foods
Broccoli Grapes Peas Apples Cereal Oatmeal
Hash browns Pizza Donuts Fried chicken French fries Hamburgers
The questions for all the healthy and unhealthy foods were identical except for the foods that were listed in each of the vignettes. Prior to the main vignettes, children were presented with two control questions with items that were unrelated to height and weight to ensure that they were familiar with the term ‘they will both grow the same’. An example of one of the vignettes for the healthy foods for height was the following: there are two boys, Brian and Nick. Brian eats all of his broccoli for dinner. Nick does not eat any of his broccoli for dinner. Who do you think is going to grow taller? (1) Brian, (2) Nick, (3) or will they both grow the same. Identical vignettes were used for the weight questions with the exception that children were asked ‘Who is going to become fatter?’ (The term ‘fatter’ was used as the youngest children in this study were familiar with this term. Pilot testing revealed that the youngest children were not familiar with other terms such as ‘heavier’ or ‘gaining weight’.)
Procedure Children were interviewed individually. They were shown hand-drawn black-and-white stick figures of the two characters in each question. The purpose of using pictures was to hold the child’s attention; the pictures did not make any reference to the height or weight of the two characters in question, and the same pictures were used for all the vignettes in both conditions. The experimenter read the vignettes to the child, pointing to the relevant card when reading the particular item. Participants were asked to answer each vignette, and their response was noted. Across all studies, the presentation of the character who ate the food and the character who did not eat the food in the response options was counterbalanced across participants within each age group so that half of the participants got the participant who ate the food first and the other half got the character who did not eat the food first. To minimize confusion for the youngest age group, the option ‘or they will both grow the same’ was always presented as the third option. For each participant, items were randomized within each condition. Adults received a testing booklet that contained the two conditions and the 12 vignettes in each condition (with no pictures) and were asked to write down their responses in the booklets.
Statistical analyses A score of 1 was assigned if participants responded that the person who ate the food would grow tall or fat, 0 was assigned if participants responded that the person who did not eat the food would grow tall or fat, and 0.5 was assigned if ‘they will grow the same’ response is selected.
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Findings from the analyses of variance A 5 (age group) 9 2 (food type) 9 2 (condition) analysis of variance (ANOVA) focusing on whether eating healthy and unhealthy food would affect height and weight was conducted. The results indicated a significant food 9 age group interaction, F(4, 131) = 2.77, p < .03, a significant condition 9 food interaction, F(1, 131) = 178.64, p < .01, and a significant condition 9 food 9 grade interaction, F(4, 131) = 22.14, p < .01. There was also a significant grade difference, F(4, 131) = 6.69, p < .01. Post-hoc Bonferroni tests indicated that overall participants recognized that healthy foods would promote a gain in height, ps < .01, whereas unhealthy foods would result in weight gain, p < .01. Post-hoc Bonferroni tests were also conducted to isolate the sources of the condition effect in the 3-way interaction. Second graders recognized that healthy foods are more likely to result in height gain, p < .05, but they did not differentiate that eating unhealthy foods would result in weight gain, p > .73. Instead, similar to preschoolers, they reasoned that eating unhealthy foods would result in an increase in both height and weight. It was only at fourth grade and older that participants consistently recognized that healthy eating would result in an increase in height, whereas unhealthy eating would result in an increase in weight, ps < .01 (see Figure 1a,b for mean growth responses across condition and grade). The results of these analyses suggest that it is only at fourth grade that children obtain a completely differentiated understanding of the impact of healthy and unhealthy nutrition on growth.
Discussion This study examined children’s recognition of the impact of healthy and unhealthy nutrition on height and weight. The most interesting part of the study was the developmental difference obtained between the younger and the older children. Preschoolers reasoned that the consumption of both healthy and unhealthy foods would result in both growing taller and fatter, similar to what Au and Romo (1999) have termed as the input–output concept where the input is food and the output is growth. However, second graders reasoned that healthy foods are more likely to promote an increase in height, but they reasoned that both healthy and unhealthy foods would result in an increase in weight. It was only at the fourth and older grades that there was evidence of a differentiation of the effects of healthy and unhealthy nutrition on height and weight. The results with younger children suggest that they demonstrate a global ontological domain in the realm of biology when assessing the impact of food on the biological process of growth (Kalish, 1997; Raman & Gelman, 2005; Wellman & Johnson, 1982). The question that these results raise is why is it that although children are receiving a plethora of information about healthy eating from the environment (Jacobson & Maxwell, 1994), they fail to differentiate between the effects of healthy and unhealthy foods on growth? First, one possible reason for this early lack of differentiation might be that the vignettes stated that one of the characters ate the food, whereas the other character did not. Thus, young children may be interpreting the vignettes to mean that the characters either ate or did not eat a food for a single meal which may not have a differentiated effect on growth which is a perfectly reasonable conclusion. However, the older children seem to infer that eating a healthy food even for one meal implies that the
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(a)
(b)
Figure 1. (a) Mean number of tall responses across grades for the consumption of healthy and unhealthy foods for Study 1. (b) Mean number of fat responses across grades for the consumption of healthy and unhealthy foods for Study 1.
person is possibly a healthy eater in general, thus affecting biological processes such as height and weight. Study 2 addresses this limitation by clearly stating the timeline of the food consumption. Second, older children may have more of an understanding of the underlying nutritional impact of the food. If this is the case, the results of Study 2 should replicate those of Study 1.
STUDY 2 In Study 2, participants were presented with identical vignettes as in Study 1, but this time the temporal timeline of the food being consumed/not consumed was clearly stated.
Method Participants The sample included 26 four- and five-year-olds (15 girls and 11 boys, M age = 4 years 5 months, range = 4 years 2 months–5 years 1 month), 26 seven- and eight-year-olds
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(10 girls and 16 boys, M age = 7 years 4 months, range = 7 years 0 month–8 years 5 months), 27 nine- and ten-year-olds (13 girls and 14 boys, M age = 9 years 4 months, range = 9 years 2 months–10 years 7 months), 25 ten- and twelve-year-olds (16 girls and 9 boys, M age = 11 years 7 months, range = 10 years 11 months–12 years 2 months), and 29 adults (22 women and 7 men, M age = 20 years 4 months, range = 18 years 2 months–48 years 0 month).
Materials The materials were identical to that of Study 1. The only difference was that the vignettes clearly stated that the characters did or did not eat food everyday (e.g., Brian eats (does not eat) all of his broccoli for dinner every day).
Procedure The procedure and coding were identical to those of Study 1.
Results from the analysis of variance A 5 (age group) 9 2 (food type) 9 2 (condition) analysis of variance (ANOVA) focusing on whether eating healthy and unhealthy food would affect height and weight was conducted. The results indicated a significant food 9 age group interaction, F(4, 128) = 3.92, p < .01, a significant condition 9 food interaction, F (1, 128) = 220.38, p < .01, and a significant condition 9 food 9 grade interaction, F (4, 128) = 37.41, p < .01. There was also a significant grade difference, F(4, 128) = 3.04, p < .02. Overall participants recognized that healthy foods would results in an increase in height, ps < .01, whereas unhealthy foods would result in an increase in weight, ps < .01. Post-hoc Bonferroni tests indicated that it was only at fourth grade and higher that children differentially recognized that healthy foods would promote a gain in height, ps < .01, whereas unhealthy foods would result in a gain in weight, ps < .01 (see Table 2 for mean growth responses across condition and grade). These results replicate the results of Study 1 because it is only at fourth grade that children consistently recognize the differential effect.
Table 2. Mean number of ‘tall’ and ‘fat’ responses (out of a maximum of 6) for each grade across conditions for Study 2 Tall Grade Preschool Second Fourth Sixth College
Fat
Healthy
Unhealthy
Healthy
Unhealthy
4.1 (1.45) 5.2 (1.48) 5.0 (1.34) 5.3 (0.86) 4.6 (1.1)
4.1 (1.15) 4.5 (1.89) 3.0 (1.92) 2.0 (1.47) 3.1 (1.31)
4.1 (1.57) 4.5 (2.19) 2.4 (1.71) 2.4 (1.57) 2.2 (1.57)
4.4 (1.23) 4.6 (1.63) 4.8 (1.38) 5.0 (1.0) 4.6 (1.44)
Note. Numbers in parenthesis indicate standard deviations.
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Discussion The results of this study replicated the results of Study 1. The most important finding is that the younger children judged that any kind of food consumption would result in growing taller and fatter. It was only at fourth grade that children consistently demonstrated a differential impact of eating healthy and unhealthy foods on height and weight. These results support the notion that children’s theory of biology undergoes a developmental shift in middle childhood. As stated earlier, one could argue that the concept of height in particular is not strongly food related but is determined by genetics (unless there are extreme conditions such as a severe lack of food) and that nutrition does not seriously impact height. However, considering that all other factors are equal, it is interesting that we observe a developmental difference in children’s reasoning about the nutritional effects of food on height and weight in middle childhood. These results raise the question as whether young children would still display an autonomous theory of biology when they have to reason about the impact of nutrition on non-biological factors such as psychological factors. Studies 3 and 4 examined whether children and adults think that healthy and/or unhealthy foods can impact the psychological domain of positive and negative mood states.
STUDY 3 The results of the first two studies lead to the question as to whether children and adults would entertain an autonomous theory of biology when reasoning about the impact of nutrition on mood states. One possibility is that even young children will keep the biological and psychological domains distinct arguing that food does not influence mood states. This position would be consistent with the distinct ontological domains theory (Gelman & Wellman, 1991; Notaro et al., 2001; Opfer, 2002). The second possibility is that there will be evidence of the domain interaction model (Nemeroff, 1995; Raman & Gelman, 2008) where children could (1) make an undifferentiated association of food with mood states or (2) show a differentiated recognition of the effects of healthy and unhealthy foods on positive and negative mood states. To test this hypotheses, Study 3 examined the effect of eating healthy and unhealthy foods on positive and negative mood states. As in Study 1, no explicit timeline for food consumption was stated in the vignettes.
Method Participants Participants in the main study were 26 four- and five-year-olds (12 girls and 14 boys, M age = 4 years 9 months, range = 4 years 5 months–5 years 4 months), 22 seven- and nine-year-olds (14 girls and 8 boys, M age = 7 years 5 months, range = 7 years 6 months–9 years 2 months), 28 nine- and ten-year-olds (13 girls and 15 boys, M age = 9 years 5 months, range = 9 years 3 months–10 years 3 months), 27 ten- and twelve-year-olds (13 girls and 14 boys, M age = 11 years 5 months, range = 10 years 11 months–12 years 6 months), and 30 adults (22 women and 8 men, M age = 19 years 6 months, range = 18 years 3 months–22 years 1 month).
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Materials The main task presented each participant with two conditions: positive mood states and negative mood states. Within each condition, each participant was presented with six vignettes describing characters who consumed the same foods as in Studies 1 and 2 (Table 3). A variety of mood states were presented because the objective of the study was to determine whether participants thought that food had an impact on mood states in general. The rationale for selecting these mood states is that it has been shown that even young children are familiar with these positive and negative mood states (Kalish, 1997; Raman & Gelman, 2004). The questions for all the healthy and unhealthy foods were identical except for the foods that were listed in each of the vignettes. An example of one of the vignettes for the healthy foods for the positive mood state was the following: There are two boys, Brian and Nick. Brian eats all of his broccoli for dinner. Nick does not eat any of his broccoli for dinner. Who do you think is going to feel more satisfied? (1) Brian; (2) Nick; (3) or will they both feel the same.
The vignette for the negative mood state was identical except that a negative mood was presented in the vignette.
Procedure and coding The procedure and coding was identical to that of Studies 1 and 2.
Results from the analysis of variance Recall that the primary interest was in determining whether children think that food can influence mood states. A 5 (age group) 9 2 (food type) 9 2 (condition) analysis of variance (ANOVA) focusing on whether eating healthy and unhealthy food would affect positive and negative mood states was conducted. The results indicated a significant main effect for mood, F(1, 128) = 459.66, p < .01, a significant condition 9 grade interaction, Table 3. (a) Positive mood states and (b) negative mood states that were paired with healthy and unhealthy foods for Studies 3 and 4
Positive mood states Satisfied Happy Excited Friendly Calm Delighted Negative mood states Sorry Guilty Angry Sad Cranky Frustrated
Healthy foods
Unhealthy foods
Broccoli Grapes Peas Apples Cereal Oatmeal
Hamburger Pizza French Fries Hash browns Donuts Fried chicken
Broccoli Grapes Peas Apples Cereal Oatmeal
Hamburger Pizza French Fries Hash browns Donuts Fried chicken
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(a)
(b)
Figure 2. (a) Mean number of responses across grades for healthy and unhealthy foods for the positive mood condition for Study 3. (b) Mean number of responses across grades for healthy and unhealthy foods for the negative mood condition for Study 3.
F(4, 128) = 21.63, p < .01, a significant condition 9 food interaction, F(1, 128) = 31.58, p < .01, and a significant condition 9 food 9 grade interaction, F(4, 128) = 2.83, p < .05. There was also a significant grade difference, F(4, 128) = 16.35, p < .01. Overall participants generated higher scores for positive mood states compared with negative mood states, ps < .01. Preschoolers associate eating healthy food with positive mood states compared with negative mood states, p < .01, but they reasoned that unhealthy food would have an effect on both positive and negative mood states, ps > .05. All other grades associated eating healthy foods with positive mood states and unhealthy foods with negative mood states, ps < .01 (Figure 2a,b).
Discussion Study 3 examined children’s and adults’ judgements about the effects of eating healthy and unhealthy foods on positive and negative mood states. In this study, even preschoolers associated eating healthy foods with positive mood states, but similar to the preschoolers in Studies 1 and 2, they judged that eating unhealthy food would have an
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impact on both positive and negative mood states. This indicates that children seem to display an earlier sensitivity to the impact of food on mood states than about the impact of food on the biological process of growth. Taken together, these results support the notion that young children entertain a cross-domain interaction model when assessing the impact of nutrition on mood states. Interestingly, young children associated eating healthy but generally distasteful foods such as broccoli as contributing to positive mood states, suggesting that they did not let their taste bias affect their judgements. The results of this study raise an interesting question as to whether children and adults would show similar patterns if they were asked what the effects of eating these foods were on a long-term daily basis. This scenario was explored in Study 4.
STUDY 4 Study 4 explores whether the long-term consumption of healthy and unhealthy foods would have an impact on mood states. There are two possible outcomes. First, older children might show similar patterns to Study 3 by associating eating healthy foods and unhealthy foods on a long-term basis with positive moods states and negative mood states, respectively. The second pattern that might emerge is that children might judge that food eaten on a long-term basis may erase some of the short-term pleasure or even create negative physical and psychological consequences.
Method Participants The sample included 24 four- and five-year-olds (11 girls and 13 boys, M age = 4 years 6 months, range = 4 years 0 month–5 years 10 month), 29 six- to nine-year-olds (13 girls and 16 boys, M age = 7 years 5 months, range = 6 years 4 months–9 years 0 month), 23 nine- and ten-year-olds (14 girls and 9 boys, M age = 9 years 7 months, range = 9 years 3 months–10 years 8 months), 31 eleven- and twelve-year-olds (11 girls and 20 boys, M age = 11 years 6 months, range = 11 years 4 months–12 years 8 months), and 27 adults (19 women and 8 men, M age = 22 years 6 months, range = 18 years 4 months– 54 years 8 months).
Materials Participants received identical vignettes as in Study 3. The one difference was that the character in each of the vignettes ate the food on a daily basis and the other character did not eat the food on a daily basis.
Procedure The procedure and the coding was identical to that of Studies 1, 2, and 3.
Results from the analysis of variance Recall that the primary interest was in determining whether children think that eating healthy/unhealthy foods on a long-term basis can influence mood states. A 5 (age
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Table 4. Mean number of ‘positive’ and ‘negative’ responses (out of a maximum of 6) for each grade across conditions for Study 4 Positive Grade Preschool Second Fourth Sixth College
Negative
Healthy
Unhealthy
Healthy
Unhealthy
2.3 (1.0) 4.8 (.91) 5.3 (0.94) 5.3 (.79) 5.0 (.77)
2.4 (0.99) 4.7 (1.0) 4.2 (1.33) 4.4 (1.25) 3.7 (1.56)
2.0 (1.41) 0.8 (0.95) 0.4 (.65) 0.6 (.88) 1.1 (1.59)
1.9 (1.17) 1.2 (1.17) 2.1 (1.54) 1.4 (1.12) 2.9 (.159)
Note. Numbers in parenthesis indicate standard deviations.
group) 9 2 (food type) 9 2 (condition) analysis of variance (ANOVA) focusing on whether eating healthy and unhealthy food would affect positive and negative mood states was conducted. The results indicated a significant main effect for mood, F(1, 129) = 527.17, p < .01, a significant condition 9 grade interaction, F(4, 129) = 26.34, p < .01, a significant condition 9 food interaction, F(1, 129) = 54.92, p < .01, and a significant condition 9 food 9 grade interaction, F(4, 129) = 8.61, p < .05. There was also a significant grade difference, F(4, 129) = 14.4, p < .01. Post-hoc Bonferroni tests revealed that overall participants generated higher means for positive mood states than for negative mood states, p < .01. Across participants, eating healthy food was associated with positive mood states and eating unhealthy food was associated with negative mood states, ps < .01. However, preschoolers did not discriminate that eating healthy foods on a long-term basis would result in positive mood states and eating unhealthy food would result in negative mood states; they reasoned that food would overall contribute to mood states, ps > .24. It was only at second grade and higher that children consistently associated eating healthy foods with positive mood states and unhealthy foods with negative mood states (see Table 4 for mean responses across grade for healthy and unhealthy foods for positive and negative mood states).
Discussion The primary purpose of Study 4 was to determine whether participants thought that eating a food on a long-term basis might have an effect on positive and/or negative mood states. The results closely replicated the results of Study 3 with the exception that preschoolers judged that when a food is consumed on a long-term basis, it will not have a differential effect on mood states. Although justifications were not asked for in these studies, some preschoolers spontaneously explained that eating something on a daily basis would not be responsible for how a person feels, but food in general (irrespective of whether it was healthy or unhealthy on a long-term basis) is likely to make a person feel good. Thus, the results of this study clearly indicate that children clearly seem to entertain a cross-domain interaction model when associating the effects of food on mood states.
GENERAL DISCUSSION Four studies examined whether children and adults demonstrated an ontologically distinct model of biology or a cross-domain interaction model when assessing the impact
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of healthy and unhealthy foods on the biological process of growth and psychological process of mood states. The results indicated that preschoolers demonstrate an ontologically distinct but undifferentiated model of biology when assessing the impact of food on growth. However, there is a developmental shift in fourth grade when children make a differential attribution of the impact of food on growth. In Study 3, preschoolers associated eating healthy foods with positive mood states, whereas they thought that eating unhealthy foods would contribute to both positive and negative mood states. In Study 4, it was only at second grade and older that children associated eating healthy foods on a long-term basis with positive mood states and unhealthy foods with negative mood states. Contrary to the work by Scott-King and Nemeroff (1989) where they found that children grow into the idea of ‘you are what you eat’ (implying that the food you ingest will result in you taking on the physical and psychological properties of that food), these results demonstrate that even young children associate the ingestion of food as having an impact on mood states. These findings suggest that young children may have a more differentiated development of a cross-domain interaction model. This might seem surprising in the light of previous research showing that children treat the biological and psychological domains as wholly distinct (Notaro, 2001). Although most studies have examined the impact of psychological factors on biological processes (Inagaki & Hatano, 1993; Notaro, Gelman, & Zimmerman, 2002) based on previous research, children would be expected to keep the two domains somewhat distinct. One possible explanation is that children demonstrate a co-existence of a theory of biology as well as a cross-domain interaction model. For example, Raman and Gelman (2008) found that young children entertain psychogenic factors as having an impact on the possibility of contracting an illness. Heyman, Phillips, and Gelman (2003) found that 5-year-olds showed systematic tendencies to take animacy into account when making predictions about principles of physics (predicting that the path an item takes when it falls will differ, depending on whether it is animate or inanimate). These findings are analogous to the findings reported in Studies 3 and 4. A second possibility is that children think that the effect of food on mood states is more immediate than the effect food has on biological processes such as growth. For example, if you eat something, you are more likely to feel satisfied or disgusted in a relatively short period of time (as opposed to eating something and growing tall or putting on weight). Thus, they might find it easier to infer that food can impact psychological mood states. The present results corroborate the suggestion that young children have a distinct ontological domains approach by the early preschool years. Preschoolers and second graders in Studies 1 and 2 did recognize that the consumption of food will result in a gain in height and weight, arguing for the notion that young children recognize that biological factors have an impact on biological processes. However, young children’s theory of biology was based on an input–output concept compared with older children, as they did not distinguish the differential effects of eating healthy and unhealthy foods on height and weight. Studies 3 and 4 presented notable findings in that even young children demonstrated a domain interaction. This is not an unreasonable association (as shown by results from other adult studies mentioned earlier) because what we eat can have physiological or psychological consequences that affect our mood states. The most pressing question is why young children seem to apply an input–output relationship when reasoning about the differential effects of eating healthy and unhealthy foods on height and weight, whereas with other biological processes such as illness, they seem to demonstrate more sophisticated reasoning even in the preschool years (Raman & Gelman, 2005). There are two possible arguments. First, children may be using a global
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input–output relationship when reasoning about the differential impact of food. Second, children might have varied developmental levels in their recognition of different biological processes (similar to Piaget’s notion of horizontal decalage). Thus, they might develop a more differentiated recognition of the mechanisms involved in illness at an earlier age than the mechanisms involved in growth. This would argue for the notion that their theory of biology is one that develops over several years starting in early childhood and well into adulthood as shown by several studies in which even adults do not show a differentiated response when reasoning about biological processes (Au & Romo, 1999; Raman & Winer, 2004). A third argument would be that the impact of food does not present a direct cause and effect relationship. Several other factors such as genetics play a major role in determining the height and weight of an individual which in turn might make differentiated reasoning about the effects of food more difficult for younger children. One difficult and unresolved question is whether one can predict in more systematic ways when children and even adults will predict that domains will interact (as in the present studies) and when children will inappropriately predict that domains will not interact (as in the Notaro et al., 2001). Both types of reasoning (although seemingly opposite) result from the same source – young children are trying to learn the extent of domain boundaries and what implications they have for reasoning. The world is complex and sometimes both domains do interact, for example one’s mood can be affected by what one eats. Interestingly, domain interaction reasoning never seems to disappear over age (as evidenced by the fact that adults also reliably associated eating healthy foods with positive mood states and unhealthy foods with negative mood states). There are some limitations to these studies. First, some might argue that the foods that are presented as healthy and unhealthy are not all truly healthy or unhealthy (e.g., fried chicken has high levels of fat but also high levels of protein; cereal is generally viewed as nutritious, but most cereals have a high amount of sugar in them). However, overall, the healthy foods presented in these studies are low in fats and sugars, whereas the unhealthy foods are high in fat. Although this distinction is not absolute, it is still a distinction that children recognize (as demonstrated with the pre-test prior to running Study 1). Second, it can be argued that the foods presented are somewhat limited in number and do not represent a large variety of healthy/unhealthy foods. The reason for this is that the number of items had to be small so that the task would not be too cognitively demanding for preschoolers. Overall, the results of these studies demonstrate that children and adults entertain a co-existence of an ontologically distinct theory of biology as well as a cross-domain interaction model when assessing the impact of nutrition on growth and mood states. These results are a first step in demonstrating the important developmental changes that are taking place between preschool and middle childhood in how children come to understand and sort out the impact of biological factors on biological and psychological processes.
Acknowledgements Preparation of this article was supported by a grant from the National Institute of Child Health and Human Development 1 R15 HD058303-01A1 to Raman. Portions of this research were presented at the 2009 Cognitive Development Society conference in San Antonio, Texas. I would like to thank the parents, children, and teachers in the Oxford School district for their participation. I also thank Jennifer Kelley and Alessa Petersen for their assistance in data
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collection. I am grateful to Todd Shackelford for his constructive comments and feedback on a draft of the manuscript.
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