Participants and the Super Diet Education (Shokuiku) Project
The Super Diet Education (Shokuiku) Project was a food education project, supported by the Japanese Ministry of Education, Culture, Science and Technology. In this project, a cross-sectional study was conducted on a cohort of elementary school children using a survey questionnaire. In total, 7,419 children aged 6–12 from 18 elementary schools in Minato City, Japan participated in the survey during 2018–2019. Cases with missing data were excluded from the analysis.
Teachers at the schools explained the purpose of the study and distributed the questionnaires, and then children and their parents completed the questionnaires and returned them to the schools. Via the questionnaires, information was collected on gender, school year (1 to 6), learning ability, physical activity, ST duration and timing, and anthropometrics. Table 1 presents a summary of the question contents and response options.
The obesity variables consisted of the BMI percentiles and Rohrer index scores, which were assessed using self-reported height and weight. In 1997, the WHO and the International Obesity Task Force adopted BMI as a valid criterion for determining childhood obesity . However, growth can affect BMI; therefore, it cannot be used in the same way in children as it can be in adults. As BMI tends to change considerably with age , the BMI percentiles were classified into two groups using age- and gender-appropriate charts  according to the following guidelines from Japan’s Ministry of Health, Labour and Welfare: “normal “(BMI ≤ 5th but < 85th percentile) and “obese” (BMI ≥ 85th percentile). The Rohrer indexes were also divided into two groups: the “obese” group, with children who had Rohrer indices ≥ 145, and the “normal” group, with those who had Rohrer indices between 115–145. The Rohrer index score was calculated as shown below .
Rohrer index = weight (kg) / height (cm)3 × 107
Large-scale population surveys, using a self-report questionnaire are the most feasible method for measuring physical activity [30,31]. The WHO Health Behaviour in School-Aged Children (HBSC) survey is one of the most comprehensive sources of data on school-aged students’ physical activity levels . The HBSC has been translated into Japanese (HBSC-J), and it has been shown to be valid . In our questionnaire, we used the following item from the HBSC to assess how often participants engaged in moderate-to-vigorous physical exercise: “In the last 7 days, how many days have you engaged in physical activities for more than 60 minutes?” The responses to this question were categorized as follows: 1 for 0 days; 2 for 1 day; 3 for 2 days; 4 for 3 days; 5 for 4 days; 6 for 5 days; 7 for 6 days; and 8 for 7 days. The responses for weekly physical activities were divided into two groups: the “high physical activities” group with children who were above the median and the “low physical activities” group, with those who were below it.
The Dry Eye-Related Quality-of-Life Score (DEQS) questionnaire was created and validated in Japan . We created the questionnaire items to assess dry eye symptoms based on the DEQS questionnaire. We asked the participants, “Do you have dry eyes?” The responses were on a scale from 1 to 4: 1, often; 2, sometimes; 3, rarely; and 4, never. “Dry eyes” responses were also divided into two groups: the “dry” group, with children who answered 1 or 2, and the “not dry” group, with those who answered 3 or 4.
The study group consisted of “class,” and “performance,” which were divided into two groups. We asked the participants, “Do you understand the material presented in your classes at school?” The answers for “class” were categorized from 1 to 4: 1, understand; 2, mostly understand; 3, slightly understand; and 4, never understand. “Class” answers were then divided into two groups: the “understand” group, with children who answered 1 or 2, and the “do not understand” group, with those who answered 3 or 4. The questions used in this item were also used in a previous study . In addition, we asked the participants, “Please describe your performance at school (in classes, on tests, etc.).” The answers for “performance” were categorized from 1 to 4: 1, perform very well; 2, perform in a satisfactory manner; 3, do not perform well; and 4, cannot perform at all. “Performance” answers were then divided into two groups: the “good” group, with children who answered 1 or 2, and the “poor” group, with those who answered 3 or 4. In Japan, where researchers’ access to children’s actual academic data is restricted, subjective learning ability is used as a feasible surrogate variable [36,37]. Self-reported grades and actual grades have previously been reported to be generally accurate .
ST duration and timing
Two items, the duration and timing of ST, were used as indicators of ST. We asked the participants, “How much time do you spend per day playing on smartphones or computers, using communication applications, playing video games, or watching TV or videos?” The responses for “duration of ST” were on a scale from 1 to 4: 1 to indicate > 5 h; 2 to indicate 3 h to < 5 h; 3 to indicate 1 h to < 3 h; and 4 to indicate < 1 h. The “duration of ST” responses were then divided into three groups: the “above 3 hours” group, with children who answered 1 or 2; the “1–3 hours” group, with those who answered 3; and the “less than 1 hour” group, with those who answered 4. The current American Academy of Pediatrics guidelines recommend that children under 2 years of age should not spend any time using electronic media, while the ST of children over 2 years of age should be kept to less than 2 hours per day [39,40]. Therefore, 2 hours is often used as a reference for ST. However, Minato City is implementing the “Minato-ku School Informatization Action Plan” and has been introducing electronic teaching materials in classes . As a result, ST among Minato City elementary school students is increasing. Considering that headaches and sleep difficulties have been reported as after more than 3 hours of ST , we used 3 hours as the ST reference, which is 1 hour more than the American Academy of Pediatrics guidelines. We asked the participants, “Just before you sleep, do you play on smartphones or computers, use communication applications, play video games, or watch TV or videos?” The responses for “timing of ST” were on a scale from 1 to 4: 1, often; 2, sometimes; 3, rarely; and 4, never. The “timing of ST” responses were then divided into two groups: the “yes” group, with children who answered 1 or 2, and the “no” group, with those who answered 3 or 4. Next, in order to examine differences in the influences of ST duration and timing, we used a combination of ST duration and timing as the explanatory variable (Table 2). For each objective variable, a logistic regression analysis comparing G1 and G2, G3 and G4, and G5 and G6 was performed.
A chi-square test was performed to compare the sex, school year, height, and weight used as confounding factors by groups. The ST in each group was examined using logistic regression analysis. First, we examined whether ST duration and timing were related to each objective variable. All variables were examined using a univariate model. Afterward, we performed multivariate logistic regression analyses for all variables that showed a significant difference in the univariate models. The odds ratios (ORs) and 95% confidence intervals (CIs) were calculated. All data were analyzed using predictive analytics software for Windows (Statistical Package for the Social Sciences; IBM Corp., Chicago, IL, USA); a p value of < 0.05 indicated statistical significance.