The demographic characteristics are summarized in Table 1. Reporting higher physical activity, being male, reporting a healthy weight, living in a large city, feeling subjectively healthy, feeling lower stress, being at a higher economic level, and having higher parental educational levels were associated with higher school performance (each with P < 0.001).
Diet habits are summarized in Table 2. The regularity of consuming breakfast, lunch, and dinner and frequency of fruit, vegetable, and milk intake were associated with higher school performance, while frequent intakes of soft drinks, fast foods, instant noodles, and confections were linked with poor school performance (each with P < 0.001). To evaluate possible associations among various dietary habits, we conducted a correlation analysis and confirmed that most of the Phi coefficients were very small (less than <0.3) (see Table S1, Supplemental Content, http://links.lww.com/MD/A845, which illustrates the Phi correlations among eating behaviors).17
We performed a multinomial logistic regression analysis adjusting for confounding factors (Table 3). In group A, compared with never eating breakfast, eating breakfast frequently showed a high AOR with a dose–response relationship (1–2 times AOR = 1.12, 95% CI = 1.05–1.19; 3–5 times AOR = 1.36, 95% CI = 1.29–1.45; 6–7 times AOR = 2.34, 95% CI = 2.20–2.48, P < 0.001). Other school performance groups (B–D) also showed dose–response relationships eating breakfast (P < 0.001). In group A, having lunch and dinner 6 to 7 times a week showed high AORs of 1.12 (95% CI = 1.00–1.26) and 1.38 (95% CI = 1.22–1.55), respectively (each with P < 0.001). However, reporting less than 6 meal times a week showed a negative relation with school performance for both lunch (1–2 times AOR = 0.74, 95% CI = 0.65–0.84; 3–5 times AOR = 0.72, 95% CI = 0.64–0.81, P < 0.001) and dinner (1–2 times AOR = 0.84, 95% CI = 0.74–0.95; 3–5 times AOR = 0.86, 95% CI = 0.76–0.97, P < 0.001).
Compared with never eating fruit, eating more was associated with group A school performance with a dose–response relationship (1–2 times AOR = 1.16, 95% CI = 1.09–1.24; 3–6 times AOR = 1.58, 95% CI = 1.48–1.68; ≥7 times AOR = 1.73, 95% CI = 1.62–1.86, P < 0.001). Similarly, frequent milk consumption was related to group A performance with a dose–response relationship (1–2 times AOR = 1.06, 95% CI = 1.00–1.12; 3–6 times AOR = 1.35, 95% CI = 1.28–1.42; ≥7 times AOR = 1.35, 95% CI = 1.28–1.43, P < 0.001). Frequent eating of vegetables was also associated with school performance with a dose–response relationship (1–2 times AOR = 1.01, 95% CI = 0.93–1.11; 3–6 times AOR = 1.24, 95% CI = 1.14–1.34; ≥7 times AOR = 1.48, 95% CI = 1.37–1.61, P < 0.001). However, consuming more soft drinks (1–2 times AOR = 0.79, 95% CI = 0.76–0.82; 3–6 times AOR = 0.59, 95% CI = 0.56–0.62; ≥7 times AOR = 0.42, 95% CI = 0.38–0.46) and instant noodles (1–2 times AOR = 0.94, 95% CI = 0.90–0.98; 3–6 times AOR = 0.67, 95% CI = 0.64–0.71; ≥7 times AOR = 0.62, 95% CI = 0.55–0.70) was negatively associated with school performance with a dose–response relationship (each with P < 0.001). Frequent fast food consumption was also negatively linked with school performance (1–2 times AOR = 0.97, 95% CI = 0.94–1.01; 3–6 times AOR = 0.75, 95% CI = 0.70–0.79; ≥7 times AOR = 0.83, 95% CI = 0.72–0.96, P < 0.001). Although eating confections less than 7 times a week did not show an evident negative relation with school performance, eating them ≥7 times a week was negatively associated with school performance (≥7 times AOR = 0.86, 95% CI = 0.80–0.93, P < 0.001).
Standardized regression weights (direct effects) are calculated. The estimated values of personal factors to diet factor, personal factors to school performance, SES to diet factors, SES to school performance, and diet factors to school performance were 0.046, 0.141, 0.140, 0.268, and 0.125, respectively (each with P < 0.001) (Table 4) (Figure 2).
The standardized total effects were calculated using direct and indirect effects. The total effects of personal factors to diet factor, personal factors to school performance, SES to diet factors, SES to school performance, and diet factors to school performance were 0.046, 0.146, 0.140, 0.285, and 0.125, respectively (Table 5) (Figure 2).
We found that the regular consumption of breakfast and frequent intake of fruits, vegetables, and milk contributed to high levels of school performance to varying degrees. Conversely, any frequency of soft drink, instant noodle, fast food intake, and eating confections ≥7 times a week negatively affected school performance. These relations between dietary habits and school performance were maintained after considering interactions with personal, socioeconomic, and dietary factors. To date, no study has comprehensively analyzed the dietary habits that are related to school performance after considering various factors. Moreover, this is the 1st study of the correlations between dietary intakes and school performance among Korean adolescents.
Of the participants, 11.8% consumed fast food more than 3 times a week in this study. This figure is comparable to that previously reported by the International Study of Asthma and Allergies in Children, which estimated that 13% of adolescents consumed fast food more than 3 times a week.19 As fast food generally contains poor nutrient content, as mentioned in the introduction, there are several concerns about the adverse outcomes of fast food. It is known that poor nutritional intakes that do not satisfy the recommended daily allowances for macro- and micronutrients are associated with significantly poorer attendance, punctuality, and grades at school, as well as with more behavior problems. These problems could be improved by adequate nutrition support in other studies of children.2,20 The poor nutritional composition of fast foods, which contain high amounts of fats and carbohydrates, may influence poor school performance. In animal and adult human studies, high fat and high carbohydrate diets are suggested to have detrimental effects on cognitive function, even after acute exposure over several days.21–23 Short-term ingestion of a high-fat diet (55% kcal from fat) impairs exercise capacity and cognitive function in both animal and adult human studies.21,23 Moreover, in animal studies, increased expression of genes related to inefficient fatty acid oxidation, such as uncoupling protein levels in mitochondria, are observed.21 These uncoupling proteins diminish metabolic efficiency (ATP production/O2 consumption), thereby impairing endurance performance.21 As fat cannot permeate the blood–brain barrier, substrate deprivation for energy production in the brain and insulin resistance are suggested as plausible mechanisms for the impaired cognitive function observed with high-fat diets.24 However, adults who consume high carbohydrate meals (54% kcal from carbohydrate) showed longer reaction times in cognitive performance tasks than those who consumed balanced meals, probably due to the increased availability of tryptophan to the serotonergic neurons involved in the sedative effect.22 A recent study experimentally proved that high saturated fat and refined carbohydrate diets induce impaired function in the frontal, limbic, and hippocampal systems, which perform learning, memory, and cognition functions.25 Several theories, including dietary-induced reductions in brain-derived neurotrophic factor (BDNF), oxidative stress, neuroinflammation, and an impaired blood–brain barrier, explain impaired brain function.25 Consistent with these theories, this study showed that fast food intake was related to poor school performance. Similarly, high carbohydrate foods, such as soft drinks and instant noodles, showed negative correlations with school performance in this study.
The relation between confections and school performance was inconsistent in this study. In 1 student study (9–22 years), it was reported that the intake of confections in the afternoon improved spatial memory, although there was contradictory results for attention.26 An afternoon snack may prevent starvation during daytime, which may impair brain function. However, confections are composed of refined carbohydrates or sugars,27 which were suggested to impair the frontal, limbic, and hippocampal systems, as well as their associated functions in learning, memory, and cognition if it is surfeited.28 Consuming confections more than 6 times a week was negatively related to school performance in this study (Table 3).
Fruits and vegetables were related to high levels of school performance. In children, a previous study demonstrated a significant correlation between executive cognitive function and snack foods but not with fruit or vegetable intakes, probably due to the small study sample and the limited number of variables considered, which might obscure the relations between fruit and vegetable consumption and executive cognitive function.29 However, several studies have demonstrated that high intakes of vegetables are related to good cognitive function in elderly populations.30,31 It was suggested that high fruit and vegetable intakes (4 or more portions/day; >350 g/day) are associated with statistically significantly increased level of antioxidants, such as carotenoids and alpha-tocopherol, whose blood levels were correlated with the results of cognitive function tests, such as the MMSE, Clock Drawing Test, and Dem Test.32 From the nutritional side, sufficient intakes of fruits and vegetables supply valuable micronutrients, such as vitamins C and E and minerals, required for brain metabolism.33 For instance, flavonoid intake dose-dependently reversed memory impairment by 40% to 70% in a mouse model.34 Moreover, because lutein and zeaxanthin are widely distributed and function in brain tissue and the macula of the retina, adequate intakes are crucial for both visual and cognitive functions throughout the lifespan.35
Milk was related to good school performance in this study. Dairy foods, including milk, were suggested to be beneficial to the neurocognitive functions of memory, vigilance, planning, and dichotic listening, probably due to better glucose tolerance in the brain and positive effects of bioactive peptides, colostrinin, proline-rich polypeptides, lactalbumin, vitamin B12, calcium, and probiotics.36
Our results showed positive relations between regular breakfast consumption and school performance in a dose-dependent manner. Several reports have suggested the beneficial effects of breakfast on cognitive performance and alertness.9,37,38 Regardless of supplement use, eating breakfast proved to be related to a smaller percentage of subjects not meeting two-thirds of the recommended daily allowance of valuable nutrients, including vitamin A (60.7% vs 43.0% for no breakfast vs breakfast, P < 0.001), vitamin C (35.6% vs 19.6% for no breakfast vs breakfast, P < 0.001), vitamin B-6 (35.6% vs 18.0% for no breakfast vs breakfast, P < 0.001), vitamin B-12 (20.7% vs 10.3% for no breakfast vs breakfast, P < 0.001), folate (23.7% vs 5.5% for no breakfast vs breakfast, P < 0.001), iron (34.8% vs 15.8% for no breakfast vs breakfast, P < 0.001), calcium (61.5% vs 38.8% for no breakfast vs breakfast, P < 0.001), phosphorus (36.3% vs 15.6% for no breakfast vs breakfast, P < 0.001), and magnesium (36.3% vs 21.4% for no breakfast vs breakfast, P < 0.001), which were difficult to compensate for through other meals in a European study.39 These results can be partially explained by the fact that eating regular breakfasts at home reduces the consumption of unhealthy snack foods during the day.40 In addition, eating breakfast may result in a more even distribution of energy and nutrient intake throughout the day. Therefore, it reduces obesity and energy shortages in the morning, which are negatively related to school performance in other studies of preschool children.41
In addition to these nutritional aspects, dietary habits themselves might influence school performance. Previous studies have demonstrated that overall diet quality, as indicated by the diet quality index, is independently related to academic performance, as subjects in 3rd (highest) diet quality index category were 30% less likely to fail a literacy assessment compared to 1st (lowest) diet quality index category (AOR = 0.70, 95% CI = 0.56–0.88).13 Dietary habits may reflect invisible factors, such as socioeconomic advantages and weight status, which can affect school performance.13 Health-related behaviors, such as eating breakfast, eating healthy foods, and avoiding junk foods, may be associated with good student compliance, which consequently improves school performance. It is possible that frequent fast food intake is correlated with undetected living circumstances, for instance, living without guidance or being of low SES.42 On the contrary, frequent breakfast intake implies that the participants live in conditions that allow and with parents who provide breakfast. It may also indicate that they are well-disciplined and self-controlled persons. It has been suggested that self-control is linked with the performance of desired behaviors and the inhibition of undesired behaviors.43 These circumstances may have significant effects on school performance by influencing school attendance, study duration, and personal characteristics such as steadiness and learning concentration. Moreover, it is possible that school performance affects dietary habits. For instance, students with good school performance might better knowledge of which dietary behaviors are good for health.
The present study, which adjusted for various factors including personal and socioeconomic factors using multinomial logistic regression analysis, is superior to previous studies. Furthermore, we adopted structural equation modeling to evaluate the relations among various personal, socioeconomic, diet factors, and school performance, thereby estimating the direct effects of diet factors on school performance (Figure 2). Diet factors influence school performance independently from the effects of other factors (direct effects) or depending on the influence of other factors (indirect effects). However, both diet factors and school performance are influenced by 3rd factors, such as personal and socioeconomic factors. For instance, socioeconomic factors are known to influence to school performance by mediating structural brain development.44 Therefore, it was possible that socioeconomic factors influence to diet factors as well as school performance and that there is no direct association between school performance and diet factors. To consider these issues, we analyzed the direct and indirect effects of each factor. Each factor demonstrated significant total and direct effects on school performance (Table 5). Personal factors showed a total effect of 0.146 and a direct effect of 0.141 on school performance. Similarly, social economic status showed a total effect of 0.285 and a direct effect of 0.268 on school performance. In comparison, the direct effect of diet factors on school performance was 0.125, which is considerable compared to those of other factors.
This study has several limitations. Although we tried to consider numerous confounding factors, including some personal and socioeconomic covariates such as region of residence, economic level, and parental education level, we cannot completely exclude the influence of these factors, such as parents’ occupations or family members living together. Moreover, as mentioned above, this study could not identify causal relations, such as possible reverse causality, due to its cross-sectional design.
As we mentioned in the method section, our classification system did not proportionally divide each level of school performance. However, this classification provided better information about the relations between the dietary habits and school performance than that obtained from a dichotomous classification. Another intrinsic limitation of this study is the accuracy of self-reported dietary consumption. As our survey investigated the frequencies of food intakes, the amounts of foods consumed could not be estimated. Moreover, because we retrieve the data only on the types of foods and there was no nutrient calculation, we were unable to quantify the nutrient exposure of the participants. However, our study population was representative of adolescents, and the survey was school based. Therefore, the reliability of the survey was predicted to be superior to those of the elderly or other general populations. Furthermore, we excluded uncompleted surveys, which might imply low confidence in the survey answers.
This study possesses considerable value due to its novel findings. This is a unique study based on a large, representative population in Korea. This study considered various kinds of foods to analyze the factors associated with school performance. Numerous covariates and their interactions are considered using standardized regression analyses, which enable us to minimize the confounding effects of other factors on the relations between certain foods or meals and school performance. Even after considering personal factors and SES, dietary habits eating fruit, soft drinks, fast foods, instant noodles, confections, vegetables, and milk consumption as well as regular consumption of breakfast, lunch, and dinner showed significant influences on school performance. Each dietary habit was independently related to school performance. Further study will be needed to elucidate the mechanisms involved in the relations between these dietary components and academic performance.
The eating 3 times per day without skipping meals, especially breakfast, and frequent intakes of fresh fruits, vegetables, and milk were related to good school performance. However, consuming several processed foods such as soft drinks, instant noodles, fast foods, and eating confections more than 7 times a week showed correlations with poor school performance. This information about dietary habits has to be considered when we educate and consult on nutrition for adolescents.
The authors thank the research grant funded by the National Research Foundation (NRF) of Korea (NRF-2015R1D1A1A01060860).
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