Skip to main content
Journal of Epidemiology logoLink to Journal of Epidemiology
. 2009 Nov 5;19(6):303–310. doi: 10.2188/jea.JE20080095

Lifestyle and Overweight Among Japanese Adolescents: The Toyama Birth Cohort Study

Yingchun Sun 1,2, Michikazu Sekine 1, Sadanobu Kagamimori 1
PMCID: PMC3924099  PMID: 19776497

Abstract

Objective

To investigate the effects of lifestyle factors on overweight among Japanese adolescents.

Methods

We studied 5753 junior high school students (2842 boys and 2911 girls) aged 12 to 13 years. The students were residents of Toyama prefecture, Japan and completed a questionnaire about their height, weight, and lifestyle factors, in June and July 2002. Subjects with a body-mass index (BMI) higher than age- and sex-specific cut-off points were defined as obese. Parental overweight was defined as a BMI of 25 or higher. Logistic regression analysis was used to examine associations between lifestyle factors and overweight.

Results

Skipping breakfast, eating quickly, excessive eating, physical inactivity, and long hours of TV watching were positively and significantly associated with overweight in both sexes. There was a negative association between snacking and overweight in girls (P < 0.001); no such association was found in boys (P > 0.05). Nighttime snacking was negatively associated with overweight in boys and girls (P < 0.05). Extended video game playing (≥2 hours; OR = 2.00, P = 0.012) and short sleep duration (<7 hours; OR = 1.81, P = 0.004) were significantly associated with overweight in girls only. The respective risks of overweight that derived from the subjects’ fathers and mothers were 2.0 and 2.5 times, respectively, in boys and 1.9 and 3.0 times in girls.

Conclusions

Parental overweight, skipping breakfast, eating quickly, excessive eating, long hours of TV watching, long hours of video game playing, physical inactivity, and short sleep duration were associated with adolescent overweight. Furthermore, there were significant negative associations between adolescent overweight and snacking in girls and nighttime snacking in both sexes.

Key words: overweight, lifestyle factors, adolescents, Japan, Toyama birth cohort study

INTRODUCTION

The proportion of children and adolescents who are overweight and obese has increased dramatically throughout the world during the past few decades.13 In Japan, the prevalence of overweight in 12-year-old and 14-year-old adolescents increased from 9.2% and 8.6% to 14.9% and 11.2%, respectively, during the period from 1976 through 2000.4 Overweight and obesity have become an overwhelming global public health issue.5

Adolescence is a critical period in the development of overweight/obesity. Obesity in adolescents is associated with several serious medical complications, including type 2 diabetes, poor immune function, hypertension, metabolic disorders, decreased mobility, and sleep apnea, and may continue into adulthood.6,7 One study found that adolescent obesity increased the long-term (approximately 50-year) risks of adult morbidity and mortality, independent of adult obesity status.8 Another study found that 70% of obese 10- to 13-year-old children become obese adults.9 Accordingly, overweight/obesity has become one of the most important issues in adolescent and adult health.

In general, the causes of overweight and obesity among children and adolescents can be divided into genetic factors, such as parental obesity,9 and lifestyle factors, which include patterns of physical activity and diet.1012 Apart from genetic factors, lifestyle is the most important factor in childhood and adolescent overweight and obesity. Some studies have shown that markers of an unhealthy lifestyle, such as inactivity, overeating, and short sleep duration, are related to overweight and obesity.1013 However, findings are not consistent among studies, due to differences in variables such as age, sex, race, and region. Therefore, more studies are needed to confirm the putative associations between lifestyle and overweight/obesity, particularly so in Japan, where the number of studies of adolescent overweight is limited.1416

In this study, we attempted to identify the associations between lifestyle factors and overweight in adolescence by surveying students aged 12 to 13 years who attended junior high schools in Toyama prefecture, Japan. In addition, differences between boys and girls were investigated.

METHODS

Subjects and procedure

The Toyama Birth Cohort Study is an ongoing follow-up study of lifestyle and health among all children born between 2 April 1989 and 1 April 1990 in Toyama Prefecture, Japan. By means of a questionnaire on lifestyle and a family history, the cohort children have been evaluated every 3 years since the inception of the study. The goal of the overall study is to clarify the effects of social, parental, and lifestyle factors on child health, and the details of this prospective study have been published elsewhere.13,17,18 The present study, which is the phase IV survey of the Toyama Birth Cohort Study, was conducted between June and July 2002. All the study subjects were aged 12 to 13 years and enrolled in the first academic year at one of 86 junior high schools in Toyama prefecture. In total, 10 453 students were included in the phase IV survey. A self-administered questionnaire was distributed throughout all junior high schools, excluding those for children with physical or mental disabilities. Of those who received a questionnaire, 9574 students (91.6%) responded. The following respondents were excluded from the analysis: those who did not answer one or more questions concerning age, gender, weight, height, the weight or height of parents, TV watching, physical activity, use of video games, eating habits, or sleeping habits. The remaining 5753 students (2842 boys and 2911 girls, 60.1% of the respondents) were the final study subjects.

The prefecture education authorities approved the content and ethical aspects of the study. Permission to participate in this follow-up study was obtained from all parents and students.

Questionnaire

Each lifestyle factor item had 4 possible responses, as follows: (1) frequency of eating breakfast, snacking, and nighttime snacking: daily, almost daily, sometimes, and rarely; (2) eating speed: very fast, fast, normal, and slow; (3) eating volume: very large, large, normal, and small; (4) frequency of physical activity: very often, often, seldom, and never; (5) hours of TV watching per day: less than 1 hour, 1 to 2 hours, 2 to 3 hours, and at least 3 hours; (6) hours of video game playing per day: do not play video games, less than 1 hour, 1 to 2 hours, and at least 2 hours; (7) usual rising time: before 6:00 AM, 6:00 to 6:30 AM, 6:30 to 7:00 AM, and after 7:00 AM; (8) usual bedtime: before 10:00 PM, 10:00 to 11:00 PM, 11:00 to 12:00 PM, and after 12:00 PM; and (9) hours of sleep per day: less than 7 hours, 7 to 8 hours, 8 to 9 hours, and at least 9 hours. In April, the weight and height of students were measured and recorded to the nearest 0.1 kg and 0.1 cm by trained school nurses using a calibrated stadiometer and beam balance. The subjects were lightly clothed in bare feet, as per School Health Law. These measurements were recorded on the questionnaire. The heights and weights of parents were self-reported in the questionnaire. The self-reported heights and weights of adults have been proven to be reliable and can be used for younger adults.19,20

The body-mass index (BMI, weight in kilograms divided by the square of height in meters) of children and their parents were calculated. Childhood overweight was determined by age- and sex-specific cut-off points that were linked to an adult BMI of 25, as developed by the Childhood Obesity Working Group of the International Obesity Task Force (IOTF).21 The cut-off points were obtained by averaging data from 6 large nationally representative surveys, including 2 reference populations from Asia. The cut-off points for BMI in children were applicable to Japanese children. In the present study, the BMI cut-off points for overweight for children were 21.22 (age 12) and 21.91 (age 13) for boys, and 21.68 (age 12) and 22.58 (age 13) for girls. Parental overweight was defined as a BMI of 25 or higher, as per the criteria of the World Health Organization.5

Statistical analysis

To better understand the associations between child lifestyle factors and overweight, we conducted a cross-sectional analysis. A longitudinal analysis of the associations of lifestyle and child overweight will be performed in a subsequent study.

The unpaired t test was used to compare differences by age, and the chi-squared test was used to evaluate the distributions of parental overweight and differences in lifestyle variables between boys and girls.

Logistic regression analysis was performed to evaluate the strength of the associations of parental overweight and lifestyle to adolescent overweight; boys and girls were analyzed separately. In model 1, logistic regression analysis was performed with adjustment for age only. In model 2, logistic regression analysis was performed with adjustment for age and parental overweight. In model 3, to control for potential confounding factors, logistic regression analysis was performed with adjustment for age, parental overweight, and other lifestyle variables. Odds ratios (OR) and 95% confidence intervals (95% CI) for overweight were calculated independently for each lifestyle variable, with dummy variables for the reference category.

Statistical analyses were conducted using SPSS 13.0. A 2-tailed P value of less than 0.05 was considered to indicate statistical significance.

RESULTS

In the comparison between boys and girls there was no significant difference in age, paternal overweight, or frequency of nighttime snacking (Table 1). The prevalence of overweight among boys was 19.0%, and was significantly higher than that among girls (13.9%; χ2 = 27.9, P < 0.001). The distributions of all other lifestyle variables and maternal overweight significantly differed by sex. As compared to boys, girls more frequently reported eating breakfast irregularly, snacking, lower physical activity levels, eating slowly, watching TV for a longer time, rising later, and sleeping less. Boys tended to eat more quickly, be more physically active, and play video games longer per day.

Table 1. Distribution of variables among the study participants, by sex.

Variables Boys (n = 2842) Girls (n = 2911) P value
Age (years), mean (sd) 12.27 (0.45) 12.25 (0.44) 0.165a
Height (cm), mean (sd) 154.2 (8.0) 152.8 (5.7) <0.001a
Weight (kg), mean (sd) 46.0 (10.2) 44.8 (8.0) <0.001a
Overweight, n (%)      
​ Yes 541 (19.0) 404 (13.9) <0.001b
​ No 2301 (81.0) 2507 (86.1)  
Paternal overweight, n (%)
​ Yes 873 (30.7) 928 (31.9) 0.342b
​ No 1969 (69.3) 1983 (68.1)  
Maternal overweight, n (%)
​ Yes 300 (10.6) 376 (12.9) 0.005b
​ No 2542 (89.4) 2535 (87.1)  
Breakfast, n (%)      
​ Daily 2558 (90.0) 2554 (87.7) 0.001b
​ Almost daily 176 (6.2) 259 (8.9)  
​ Sometimes 76 (2.7) 77 (2.6)  
​ Rarely 32 (1.1) 21 (0.7)  
Snacking, n (%)      
​ Daily 658 (23.2) 676 (23.2) <0.001b
​ Almost daily 962 (33.8) 1183 (40.6)  
​ Sometimes 673 (23.7) 633 (21.7)  
​ Rarely 549 (19.3) 419 (14.4)  
Nighttime snacking, n (%)
​ Daily 661 (23.3) 638 (21.9) 0.144b
​ Almost daily 252 (8.9) 286 (9.8)  
​ Sometimes 516 (18.2) 485 (16.7)  
​ Rarely 1413 (49.7) 1502 (51.6)  
Eating speed, n (%)      
​ Very fast 184 (6.5) 51 (1.8) <0.001b
​ Fast 862 (30.3) 461 (15.8)  
​ Normal 1488 (52.4) 1883 (64.7)  
​ Slow 308 (10.8) 516 (17.7)  
Eating volume, n (%)      
​ Very large 171 (6.0) 52 (1.8) <0.001b
​ Large 772 (27.2) 459 (15.8)  
​ Normal 1687 (59.4) 2086 (71.7)  
​ Small 212 (7.5) 314 (10.8)  
Physical activity, n (%)
​ Very often 893 (31.4) 496 (17.0) <0.001b
​ Often 1301 (45.8) 1220 (41.9)  
​ Seldom 578 (20.3) 1024 (35.2)  
​ Almost never 70 (2.5) 171 (5.9)  
TV watching (hours), n (%)
​ <1 410 (14.4) 421 (14.5) <0.001b
​ 1–2 1150 (40.5) 1063 (36.5)  
​ 2–3 799 (28.1) 772 (26.5)  
​ ≥3 483 (17.0) 655 (22.5)  
Video game playing (hours), n (%)
​ 0 608 (21.4) 1681 (57.7) <0.001b
​ <1 1208 (42.5) 840 (28.9)  
​ 1–2 789 (27.8) 291 (10.0)  
​ ≥2 237 (8.3) 99 (3.4)  
Rising time, n (%)      
​ Before 6:00 AM 220 (7.7) 167 (5.7) <0.001b
​ 6:00–6:30 AM 905 (31.8) 962 (33.0)  
​ 6:30–7:00 AM 1204 (42.4) 1371 (47.1)  
​ After 7:00 AM 513 (18.1) 411 (14.1)  
Bedtime, n (%)      
​ Before 22:00 PM 716 (25.2) 396 (13.6) <0.001b
​ 22:00–23:00 PM 1431 (50.4) 1404 (48.2)  
​ 23:00–0:00 PM 583 (20.5) 926 (31.8)  
​ After 0:00 PM 112 (3.9) 185 (6.4)  
Sleep duration (hours), n (%)
​ <7 385 (13.5) 646 (22.2) <0.001b
​ 7–8 1221 (43.0) 1376 (47.3)  
​ 8–9 989 (34.8) 751 (25.8)  
​ ≥9 247 (8.7) 138 (4.7)  

at-test

bPearson chi-square test

Tables 2 and 3 show the associations between lifestyle variables and overweight in Japanese junior high school students. Skipping breakfast, eating fast, excessive eating, physical inactivity, and long hours of TV watching were all positively and significantly associated with overweight in both boys and girls in all models. Although there was a negative association between snacking and overweight in girls (P < 0.001), no such association was found in boys (P > 0.05). Nighttime snacking was negatively associated with overweight in boys and girls in all models (P < 0.05). No significant association between either rising time or bedtime and overweight was found for either sex in the 3 models (data not shown). Although long hours of video game playing and short sleep duration were significantly associated with overweight in both sexes, the associations disappeared in boys after adjustment for age, parental overweight, and other lifestyle factors. We also found that parental overweight was strongly associated with overweight in their children. In boys, the risks of overweight derived from their fathers and mothers were 2.0 times and 2.5 times, respectively; the corresponding values in girls were 1.9 times and 3.0 times.

Table 2. Associations between lifestyles and overweight in boys aged 12–13 (n = 2842).

Variables Not overweight
(n = 2301)
n (%)
Overweight
(n = 541)
n (%)
Model 1 Model 2 Model 3



OR (95%CI) P value OR (95%CI) P value OR (95%CI) P value
Father                
​ Overweight 631 (27.4) 242 (44.7) 2.10 (1.73–2.55) <0.001 1.97 (1.59–2.45) <0.001
​ Not overweight 1670 (72.6) 299 (55.3) 1.00       1.00  
Mother                
​ Overweight 190 (8.3) 110 (20.3) 2.78 (2.14–3.61) <0.001 2.49 (1.85–3.34) <0.001
​ Not overweight 2111 (91.7) 431 (79.7) 1.00       1.00  
Breakfast                
​ Daily 2091 (90.9) 467 (86.3) 1.00   1.00   1.00  
​ Almost daily 131 (5.7) 45 (8.3) 1.53 (1.08–2.18) 0.018 1.50 (1.04–2.16) 0.030 1.85 (1.23–2.79) 0.003
​ Sometimes 57 (2.5) 19 (3.5) 1.50 (0.89–2.55) 0.130 1.51 (0.88–2.60) 0.135 1.49 (0.80–2.77) 0.206
​ Rarely 22 (1.0) 10 (1.8) 2.02 (0.95–4.30) 0.068 1.97 (0.90–4.30) 0.090 2.59 (1.05–6.40) 0.039
Snacking                
​ Daily 543 (23.6) 115 (21.3) 0.89 (0.66–1.19) 0.420 0.86 (0.64–1.16) 0.338 0.80 (0.57–1.12) 0.186
​ Almost daily 800 (34.8) 162 (29.9) 0.85 (0.65–1.12) 0.250 0.83 (0.63–1.10) 0.188 0.82 (0.60–1.12) 0.212
​ Sometimes 515 (22.4) 158 (29.2) 1.29 (0.98–1.70) 0.070 1.22 (0.92–1.62) 0.165 1.14 (0.83–1.56) 0.427
​ Rarely 443 (19.3) 106 (19.6) 1.00   1.00   1.00  
Nighttime snacking
​ Daily 555 (24.1) 106 (19.6) 0.72 (0.56–0.92) 0.008 0.70 (0.55–0.90) 0.006 0.64 (0.49–0.85) 0.002
​ Almost daily 213 (9.3) 39 (7.2) 0.69 (0.48–0.99) 0.044 0.68 (0.47–0.99) 0.043 0.66 (0.44–0.99) 0.042
​ Sometimes 418 (18.2) 98 (18.1) 0.88 (0.68–1.14) 0.334 0.93 (0.71–1.20) 0.563 0.88 (0.66–1.18) 0.408
​ Rarely 1115 (48.5) 298 (55.1) 1.00   1.00   1.00  
Eating speed                
​ Very fast 113 (4.9) 71 (13.1) 10.31 (5.88–18.09) <0.001 10.44 (5.91–18.45) <0.001 4.16 (2.22–7.82) <0.001
​ Fast 622 (27.0) 240 (44.4) 6.32 (3.84–10.42) <0.001 5.96 (3.60–9.88) <0.001 3.33 (1.94–5.72) <0.001
​ Normal 1276 (55.5) 212 (39.2) 2.71 (1.64–4.45) <0.001 2.68 (1.62–4.42) <0.001 2.32 (1.36–3.95) 0.002
​ Slow 290 (12.6) 18 (3.3) 1.00   1.00   1.00  
Eating volume                
​ Very large 92 (4.0) 79 (14.6) 22.66 (10.51–48.88) <0.001 21.11 (9.72–45.84) <0.001 15.7 (6.93–35.83) <0.001
​ Large 510 (22.2) 262 (48.4) 13.61 (6.60–28.03) <0.001 12.74 (6.15–26.35) <0.001 9.54 (4.50–20.23) <0.001
​ Normal 1495 (65.0) 192 (35.5) 3.32 (1.61–6.85) 0.001 3.22 (1.56–6.65) 0.002 2.65 (1.26–5.57) 0.010
​ Small 204 (8.9) 8 (1.5) 1.00   1.00   1.00  
Physical activity                
​ Very often 792 (34.4) 101 (18.7) 1.00   1.00   1.00  
​ Often 1035 (45.0) 266 (49.2) 2.00 (1.56–2.56) <0.001 2.00 (1.55–2.57) <0.001 2.23 (1.70–2.94) <0.001
​ Seldom 429 (18.6) 149 (27.5) 2.71 (2.05–3.58) <0.001 2.65 (1.99–3.52) <0.001 2.82 (2.05–3.87) <0.001
​ Never 45 (2.0) 25 (4.6) 4.30 (2.53–7.32) <0.001 4.28 (2.48–7.38) <0.001 4.38 (2.34–8.19) <0.001
TV watching (hours)
​ <1 349 (15.2) 61 (11.3) 1.00   1.00   1.00  
​ 1–2 951 (41.3) 199 (36.8) 1.21 (0.88–1.65) 0.241 1.20 (0.88–1.66) 0.251 1.28 (0.90–1.82) 0.173
​ 2–3 644 (28.0) 155 (28.7) 1.38 (1.00–1.91) 0.049 1.40 (1.00–1.94) 0.047 1.29 (0.89–1.87) 0.173
​ ≥3 357 (15.5) 126 (23.3) 2.06 (1.47–2.90) <0.001 1.96 (1.38–2.77) <0.001 1.79 (1.21–2.67) 0.004
Video game playing (hours)
​ 0 508 (22.1) 100 (18.5) 1.00   1.00   1.00  
​ <1 1002 (43.5) 206 (38.1) 1.04 (0.80–1.35) 0.757 1.03 (0.79–1.34) 0.831 0.88 (0.66–1.18) 0.402
​ 1–2 611 (26.6) 178 (32.9) 1.47 (1.12–1.93) 0.005 1.45 (1.10–1.91) 0.009 1.12 (0.82–1.53) 0.469
​ ≥2 180 (7.8) 57 (10.5) 1.62 (1.12–2.33) 0.010 1.50 (1.03–2.20) 0.034 0.91 (0.59–1.41) 0.675
Sleep duration (hours)
​ <7 291 (12.6) 94 (17.4) 1.50 (1.13–1.99) 0.006 1.42 (1.06–1.90) 0.019 1.21 (0.82–1.77) 0.333
​ 7–8 991 (43.1) 230 (42.5) 1.08 (0.87–1.34) 0.513 1.04 (0.83–1.30) 0.744 0.97 (0.75–1.26) 0.819
​ 8–9 812 (35.3) 177 (32.7) 1.00   1.00   1.00  
​ ≥9 207 (9.0) 40 (7.4) 0.88 (0.61–1.29) 0.521 0.90 (0.61–1.32) 0.584 0.71 (0.46–1.10) 0.126

OR: odds ratio; 95% CI: 95% confidence interval

Model 1: ORs were adjusted for age.

Model 2: ORs were adjusted for age, paternal overweight, and maternal overweight.

Model 3: ORs were adjusted for age, paternal overweight, maternal overweight, and other lifestyle variables.

Table 3. Associations between lifestyles and overweight in girls aged 12–13 (n = 2911).

Variables Not overweight
(n = 2507)
n (%)
Overweight
(n = 404)
n (%)
Model 1 Model 2 Model 3



OR (95%CI) P value OR (95%CI) P value OR (95%CI) P value
Father                
​ Overweight 746 (29.8) 182 (45.0) 1.84 (1.49–2.31) <0.001 1.89 (1.50–2.38) <0.001
​ Not overweight 1761 (70.2) 222 (55.0) 1.00       1.00  
Mother                
​ Overweight 260 (10.4) 116 (28.7) 3.39 (2.63–4.37) <0.001 3.03 (2.30–3.98) <0.001
​ Not overweight 2247 (89.6) 288 (71.3) 1.00       1.00  
Breakfast                
​ Daily 2219 (88.5) 335 (82.9) 1.00   1.00   1.00  
​ Almost daily 216 (8.6) 43 (10.6) 1.32 (0.93–1.86) 0.119 1.32 (0.92–1.88) 0.133 1.19 (0.81–1.76) 0.373
​ Sometimes 60 (2.4) 17 (4.2) 1.88 (1.08–3.26) 0.025 1.96 (1.11–3.45) 0.020 1.76 (0.95–3.26) 0.073
​ Rarely 12 (0.5) 9 (2.2) 4.96 (2.08–11.87) <0.001 5.14 (2.10–12.57) <0.001 7.93 (2.79–22.53) <0.001
Snacking                
​ Daily 618 (24.7) 58 (14.4) 0.37 (0.26–0.53) <0.001 0.38 (0.26–0.55) <0.001 0.31 (0.21–0.47) <0.001
​ Almost daily 1049 (41.8) 134 (33.2) 0.50 (0.37–0.68) <0.001 0.50 (0.37–0.689) <0.001 0.45 (0.32–0.63) <0.001
​ Sometimes 506 (20.2) 127 (31.4) 0.98 (0.72–1.34) 0.909 0.97 (0.70–1.33) 0.839 0.93 (0.66–1.30) 0.667
​ Rarely 334 (13.3) 85 (21.0) 1.00   1.00   1.00  
Nighttime snacking
​ Daily 559 (22.3) 79 (19.6) 0.76 (0.58–1.00) 0.050 0.80 (0.61–1.06) 0.121 0.88 (0.65–1.19) 0.401
​ Almost daily 253 (10.1) 33 (8.2) 0.70 (0.48–1.04) 0.077 0.71 (0.47–1.05) 0.085 0.68 (0.44–1.04) 0.074
​ Sometimes 428 (17.1) 57 (14.1) 0.72 (0.53–0.98) 0.035 0.77 (0.56–1.06) 0.105 0.70 (0.50–0.98) 0.038
​ Rarely 1267 (50.5) 235 (58.2) 1.00   1.00   1.00  
Eating speed                
​ Very fast 41 (1.6) 10 (2.5) 3.06 (1.42–6.58) 0.004 3.11 (1.42–6.77) 0.004 2.92 (1.23–6.91) 0.015
​ Fast 354 (14.1) 107 (26.5) 3.82 (2.58–5.68) <0.001 3.61 (2.41–5.40) <0.001 2.55 (1.65–3.96) <0.001
​ Normal 1634 (65.2) 249 (61.6) 1.92 (1.34–2.74) <0.001 1.79 (1.24–2.56) 0.002 1.69 (1.15–2.47) 0.007
​ Slow 478 (19.1) 38 (9.4) 1.00   1.00   1.00  
Eating volume                
​ Very large 42 (1.7) 10 (2.5) 4.50 (1.92–10.57) 0.001 4.46 (1.87–10.66) 0.001 4.26 (1.63–11.13) 0.003
​ Large 350 (14.0) 109 (27.0) 5.86 (3.39–10.13) <0.001 5.56 (3.19–9.68) <0.001 5.47 (3.01–9.94) <0.001
​ Normal 1817 (72.5) 269 (66.6) 2.77 (1.65–4.66) <0.001 2.57 (1.52–4.34) <0.001 2.70 (1.55–4.70) <0.001
​ Small 298 (11.9) 16 (4.0) 1.00   1.00   1.00  
Physical activity                
​ Very often 458 (18.3) 38 (9.4) 1.00   1.00   1.00  
​ Often 1058 (42.2) 162 (40.1) 1.85 (1.28–2.67) 0.001 1.78 (1.22–2.59) 0.003 1.88 (1.27–2.78) 0.002
​ Seldom 855 (34.1) 169 (41.8) 2.39 (1.65–3.45) <0.001 2.21 (1.51–3.21) <0.001 2.35 (1.58–3.48) <0.001
​ Never 136 (5.4) 35 (8.7) 3.11 (1.89–5.12) <0.001 2.88 (1.73–4.80) <0.001 3.61 (2.10–6.20) <0.001
TV watching (hours)
​ <1 383 (15.3) 38 (9.4) 1.00   1.00   1.00  
​ 1–2 939 (37.5) 124 (30.7) 1.33 (0.91–1.95) 0.143 1.31 (0.88–1.93) 0.179 1.40 (0.93–2.11) 0.103
​ 2–3 655 (26.1) 117 (29.0) 1.80 (1.22–2.65) 0.003 1.80 (1.21–2.68) 0.003 1.95 (1.29–2.96) 0.002
​ ≥3 530 (21.1) 125 (30.9) 2.39 (1.62–3.51) <0.001 2.34 (1.58–3.47) <0.001 2.37 (1.55–3.62) <0.001
Video game playing (hours)
​ 0 1474 (58.8) 207 (51.2) 1.00   1.00   1.00  
​ <1 713 (28.4) 127 (31.4) 1.27 (1.00–1.61) 0.052 1.26 (0.99–1.61) 0.065 1.16 (0.90–1.51) 0.257
​ 1–2 246 (9.8) 45 (11.1) 1.30 (0.92–1.85) 0.138 1.32 (0.92–1.88) 0.133 1.07 (0.73–1.57) 0.726
​ ≥2 74 (3.0) 25 (6.2) 2.42 (1.50–3.90) <0.001 2.41 (1.48–3.94) <0.001 2.00 (1.17–3.43) 0.012
Sleep duration (hours)
​ <7 537 (21.4) 109 (27.0) 1.62 (1.19–2.20) 0.002 1.63 (1.19–2.24) 0.002 1.81 (1.21–2.72) 0.004
​ 7–8 1188 (47.4) 188 (46.5) 1.26 (0.96–1.65) 0.103 1.33 (1.01–1.77) 0.045 1.37 (1.00–1.88) 0.049
​ 8–9 667 (26.6) 84 (20.8) 1.00   1.00   1.00  
​ ≥9 115 (4.6) 23 (5.7) 1.59 (0.96–2.62) 0.071 1.69 (1.01–2.83) 0.045 1.53 (0.87–2.69) 0.137

OR: odds ratio; 95% CI: 95% confidence interval

Model 1: ORs were adjusted for age.

Model 2: ORs were adjusted for age, paternal overweight, and maternal overweight.

Model 3: ORs were adjusted for age, paternal overweight, maternal overweight, and other lifestyle variables.

DISCUSSION

Many studies have reported that parental obesity, irregular diet, sedentary behavior, and poor sleep are associated with childhood and adolescent obesity.10,13,17,22 Consistent with these studies, we found that parental overweight, skipping breakfast, eating quickly, excessive eating, long hours of TV watching, long hours of video game playing, physical inactivity, and, in girls, short sleep duration were associated with adolescent overweight. Furthermore, we also found significant negative associations between adolescent overweight and snacking in girls and nighttime snacking in both sexes.

Earlier studies reported that overweight/obese children are inclined to have breakfast less frequently than normal weight children, and that when they eat breakfast, overweight/obese children have lower energy intakes and consume fewer nutrients than do normal weight children.23,24 Among children, skipping breakfast appears to be associated with a higher intake of high calorie foods and lower intakes of protein, vitamins, and minerals.25 Also, adolescents who ate less cereal and milk had a higher percentage of body fat.26 Thus, it has been widely assumed that skipping breakfast may lead to excessive weight gain. Our data confirmed that among adolescents who skipped breakfast there was a statistically significant prevalence of overweight. We affirm that skipping breakfast is an important determinant of adolescent overweight/obesity. Conversely, eating breakfast has been shown to reduce dietary fat.27 Moreover, starting each day with breakfast helps meet the recommended dietary allowances for vitamins A, B-6, and D, calcium, magnesium, riboflavin, zinc, phosphorus, and iron.25,28 Furthermore, in our study, overweight girls were prevalent among breakfast skippers. It is possible that in an attempt to control their body weight, adolescent girls do not eat breakfast.

With regard to other dietary habits, we found that excessive eating and eating quickly were associated with adolescent overweight. One explanation for this may be that excessive eating and rapid eating increase the amount of food entering the body, which leads to excessive energy intake, disruption of the energy balance in the body, and, ultimately, weight gain. Snacking is often looked upon as a source of excess caloric intake that contributes to an undesirable weight profile, and some studies have supported this opinion.29,30 However, the association between snacking and body weight is not consistent across studies.31 A review conducted by Cees de Graaf 32 found that the regularity of snacking was the essential determinant of adiposity. Because snacks are generally consumed on a more irregular basis than meals, people do not compensate for the energy intake from snacks consumed on an irregular basis. However, these explanations do not explain the negative association between snacks (including nighttime snacks) and adolescent overweight that was observed in the present study. A potential reason for our result is that adolescent changes in body composition cause boys to rapidly reduce body fat mass and girls aged 12 to 13 years—who are at peak height velocity—to quickly gain height. The energy intake from snacks or nighttime snacks may not be accumulated as excess energy in the body, but is instead absorbed for the development of the body during the adolescent growth spurt. Another potential reason is that snacks may contain little energy: greater general knowledge of prevention of overweight and obesity, and girls’ preferences regarding body shape, may encourage children to select low calorie foods when they snack. In a short-term intervention study, some researchers demonstrated that low calorie snacks could reduce the risk of overweight and obesity. Waller et al33 suggested that, among overweight or obese nighttime snackers, eating cereal after the evening meal reduced post-dinner energy intake and total daily caloric intake, and resulted in weight loss. The results of the present study support this earlier finding. Taken as a whole, these results provide new insight into the prevention of overweight and obesity, ie, adiposity can also be prevented or reduced by changing the composition of snacks, not just by changing snacking behavior.

As noted above, sedentary lifestyle patterns in children and adolescents have been associated with obesity. It is believed that the increased use of information and communication technology—particularly watching television, playing video games, and using computers—significantly contributes to a sedentary lifestyle, and thus to the increasing prevalence of obesity.34,35 In our study, playing video games (in girls), watching TV, and limited physical activity were strongly associated with overweight; however, playing video games in boys showed no such association after adjustment for other lifestyle factors. One reasonable explanation for this is that boys offset sedentary behaviors with higher physical activity levels. Indeed, boys (31.4%) were more active than girls (17.0%) in this study. Another possible explanation is that boys prefer video games with shooting, fighting, sports, and driving, while girls prefer adventure video games,36 which may result in different energy expenditures.37

Some epidemiological investigations have demonstrated that short sleep duration is a strong predictor of overweight/obesity13,38,39 and that there is sex difference in the relation between sleep duration and overweight/obesity.38,40 In contrast with the findings of Eisenmann JC et al,38 we found that short sleep duration (<7 hours or 7–8 hours) was associated with overweight in girls, but not in boys. In contrast with our findings from phase II, when children in the Toyama Birth Cohort Study were aged 6 and 7 years,13 the present study found no significant positive association between short sleep duration and overweight in boys. We believe that the difference in the association between sleep duration and childhood overweight may be due to gender differences in the physiological mechanisms of puberty, particularly with regard to changes in body composition. During puberty, the growth rates and hormone secretion levels of males and females differ.41 Males rapidly increase muscle mass and reduce body fat mass, due to increases in testosterone, growth hormone, and insulin-like growth factor-1.41,42 Females, on the other hand, experience rapid increases in fat mass during puberty, which may be largely due to increases in estradiol.42,43 These sex-specific effects on the endocrine system and metabolism explain why sleep duration has a different impact on weight gain in boys and girls.

It should be noted that our study has several limitations. First, the use of a cross-sectional study design precludes determination of the temporal sequence of lifestyle and overweight. Second, this study focused on a relatively narrow age range (12–13 years) of adolescents in Toyama Prefecture, Japan, and may not be nationally representative. Third, our interpretations in this study are limited to junior high school students who completed the study survey. Moreover, because items regarding total calorie intake and soft drinks were not included in the present study, the associations between dietary habits and adolescent overweight should be interpreted cautiously. Some of the lifestyle questionnaire items may be considered vague, which may lead to nondifferential misclassifications. However, because nondifferential misclassifications generally dilute the magnitude of the associations of factors with outcomes, the true relationship of factors and outcomes may be stronger than the observed relationship. Nonetheless, the findings from this study contribute to the body of evidence indicating that adolescents continue to require interventions that target multiple aspects of diet, physical activity, and sedentary and sleep behaviors. Such interventions would be likely to increase the proportion of adolescents who meet recommended health guidelines.

CONCLUSIONS

This study showed that parental overweight, skipping breakfast, eating quickly, excessive eating, long hours of TV watching, long hours of video game playing, physical inactivity, and short sleep duration were associated with adolescent overweight. Furthermore, significant negative associations were found between adolescent overweight and snacking among girls and nighttime snacking among both sexes.

ACKNOWLEDGMENTS

We are indebted to the Toyama Society of School Health for agreeing to cooperate with this study, and to all the members of the Toyama Birth Cohort Study team. We express our great appreciation to all the children and their parents who participated in this study and to the principals and school nurses in Toyama Prefecture for their help and cooperation in administering the study. We also acknowledge the contribution of Yasuko Yamazaki in collecting and managing the data for this study. This study was supported by grants from the Ministry of Health, Labour and Welfare (H13-Health-022), the Toyama Medical Association, and the Japan Heart Foundation. Funding organizations were not involved in the design, conduct, interpretation, or analysis of the study; nor did they review or approve this manuscript. We report no conflicts of interest, including directorships, stock holdings, or contracts.

REFERENCES

  • 1.Wang Y , Monteiro C , Popkin BM. Trends of obesity and underweight in older children and adolescents in the United States, Brazil, China, and Russia . Am J Clin Nutr. 2002;75(6):971–7 [DOI] [PubMed] [Google Scholar]
  • 2.Lissau I , Overpeck MD , Ruan WJ , Due P , Holstein BE , Hediger ML. Body mass index and overweight in adolescents in 13 European countries, Israel, and the United States . Arch Pediatr Adolesc Med. 2004;158(1):27–33 10.1001/archpedi.158.1.27 [DOI] [PubMed] [Google Scholar]
  • 3.Wang Y , Lobstein T. Worldwide trend in childhood overweight and obesity . Int J Pediatr Obes. 2006;1(1):11–25 10.1080/17477160600586747 [DOI] [PubMed] [Google Scholar]
  • 4.Matsushita Y , Yoshiike N , Kaneda F , Yoshita K , Takimoto H. Trends in childhood obesity in Japan over the last 25 years from the national nutrition survey . Obes Res. 2004;12(2):205–14 10.1038/oby.2004.27 [DOI] [PubMed] [Google Scholar]
  • 5.World Health Organization. Obesity: Preventing and Managing the Global Epidemic. Report of a WHO Consultation presented at the World Health Organization, June 3–5. Publication WHO/NUT/NCD: Geneva; 1998. [PubMed] [Google Scholar]
  • 6.Wabitsch M Overweight and obesity in European children: definition and diagnostic procedures, risk factors and consequences for later health outcome . Eur J Pediatr. 2000;159suppl 1:S8–13 10.1007/PL00014368 [DOI] [PubMed] [Google Scholar]
  • 7.Freedman DS , Khan LK , Serdula MK , Dietz WH , Srinivasan SR , Berenson GS. Inter-relationships among childhood BMI, childhood height, and adult obesity: the Bogalusa Heart Study . Int J Obes Relat Metab Disord. 2004;28(1):10–6 10.1038/sj.ijo.0802544 [DOI] [PubMed] [Google Scholar]
  • 8.Must A , Jacques PF , Dallal GE , Bajema CJ , Dietz WH. Long-term morbidity and mortality of overweight adolescents. A follow-up of the Harvard Growth Study of 1922 to 1935 . N Engl J Med. 1992;327(19):1350–5 [DOI] [PubMed] [Google Scholar]
  • 9.Whitaker RC , Wright JA , Pepe MS , Seidel KD , Dietz WH. Predicting obesity in young adulthood from childhood and parental obesity . N Engl J Med. 1997;337(13):869–73 10.1056/NEJM199709253371301 [DOI] [PubMed] [Google Scholar]
  • 10.Burke V , Beilin LJ , Durkin K , Stritzke WG , Houghton S , Cameron CA. Television, computer use, physical activity, diet and fatness in Australian adolescents . Int J Pediatr Obes. 2006;1(4):248–55 10.1080/17477160600984975 [DOI] [PubMed] [Google Scholar]
  • 11.Janssen I , Katzmarzyk PT , Boyce WF , King MA , Pickett W. Overweight and obesity in Canadian adolescents and their associations with dietary habits and physical activity patterns . J Adolesc Health. 2004;35(5):360–7 [DOI] [PubMed] [Google Scholar]
  • 12.Patrick K , Norman GJ , Calfas KJ , Sallis JF , Zabinski MF , Rupp J , et al. . Diet, physical activity, and sedentary behaviors as risk factors for overweight in adolescence . Arch Pediatr Adolesc Med. 2004;158(4):385–90 10.1001/archpedi.158.4.385 [DOI] [PubMed] [Google Scholar]
  • 13.Sekine M , Yamagami T , Handa K , Saito T , Nanri S , Kawaminami K , et al. . A dose–response relationship between short sleeping hours and childhood obesity: results of the Toyama birth cohort study . Child Care Health Dev. 2002;28(2):163–70 10.1046/j.1365-2214.2002.00260.x [DOI] [PubMed] [Google Scholar]
  • 14.Baba R , Iwao N , Koketsu M , Nagashima M , Inasaka H. Risk of obesity enhanced by poor physical activity in high school students . Pediatr Int. 2006;48(3):268–73 10.1111/j.1442-200X.2006.02202.x [DOI] [PubMed] [Google Scholar]
  • 15.Wang H , Sekine M , Chen X , Kanayama H , Yamagami T , Kagamimori S. Sib-size, birth order and risk of overweight in junior high school students in Japan: results of the Toyama Birth Cohort Study . Prev Med. 2007;44(1):45–51 10.1016/j.ypmed.2006.07.015 [DOI] [PubMed] [Google Scholar]
  • 16.Yuasa K , Sei M , Takeda E , Ewis AA , Munakata H , Onishi C , et al. . Effects of lifestyle habits and eating meals together with the family on the prevalence of obesity among school children in Tokushima, Japan: a cross-sectional questionnaire-based survey . J Med Invest. 2008;55(1–2):71–7 10.2152/jmi.55.71 [DOI] [PubMed] [Google Scholar]
  • 17.Takahashi E , Yoshida K , Sugimori H , Miyakawa M , Izuno T , Yamagami T , et al. . Influence factors on the development of obesity in 3-year-old children based on the Toyama study . Prev Med. 1999;28(3):293–6 10.1006/pmed.1998.0428 [DOI] [PubMed] [Google Scholar]
  • 18.Kagamimori S , Yamagami T , Sokejima S , Numata N , Handa K , Nanri S , et al. . The relationship between lifestyle, social characteristics and obesity in 3-year-old Japanese children . Child Care Health Dev. 1999;25(3):235–47 10.1046/j.1365-2214.1999.00127.x [DOI] [PubMed] [Google Scholar]
  • 19.Wada K , Tamakoshi K , Tsunekawa T , Otsuka R , Zhang H , Murata C , et al. . Validity of self-reported height and weight in a Japanese workplace population . Int J Obes (Lond). 2005;29(9):1093–9 10.1038/sj.ijo.0803012 [DOI] [PubMed] [Google Scholar]
  • 20.Kuczmarski MF , Kuczmarski RJ , Najjar M. Effects of age on validity of self-reported height, weight, and body mass index: findings from the Third National Health and Nutrition Examination Survey, 1988–1994 . J Am Diet Assoc. 2001;101(1):28–34 10.1016/S0002-8223(01)00008-6 [DOI] [PubMed] [Google Scholar]
  • 21.Cole TJ , Bellizzi MC , Flegal KM , Dietz WH. Establishing a standard definition for child overweight and obesity worldwide: international survey . BMJ. 2000;320(7244):1240–3 10.1136/bmj.320.7244.1240 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Kuriyan R , Bhat S , Thomas T , Vaz M , Kurpad AV. Television viewing and sleep are associated with overweight among urban and semi-urban South Indian children . Nutr J. 2007;6:25 10.1186/1475-2891-6-25 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Ortega RM , Requejo AM , Lopez-Sobaler AM , Quintas ME , Andres P , Redondo MR , et al. . Difference in the breakfast habits of overweight/obese and normal weight schoolchildren . Int J Vitam Nutr Res. 1998;68(2):125–32 [PubMed] [Google Scholar]
  • 24.Summerbell CD , Moody RC , Shanks J , Stock MJ , Geissler C. Relationship between feeding pattern and BMI in 220 free-living people in four age groups . Eur J Clin Nutr. 1996;50(8):513–9 [PubMed] [Google Scholar]
  • 25.Nicklas TA , Reger C , Myers L , O’Neil C. Breakfast consumption with and without vitamin–mineral supplement use favorably impacts daily nutrient intake of ninth-grade students . J Adolesc Health. 2000;27(5):314–21 10.1016/S1054-139X(00)00113-0 [DOI] [PubMed] [Google Scholar]
  • 26.Baric IC , Cvjetic S , Satalic Z. Dietary intakes among Croatian schoolchildren and adolescents . Nutr Health. 2001;15(2):127–38 [DOI] [PubMed] [Google Scholar]
  • 27.Siega-Riz AM , Popkin BM , Carson T. Trends in breakfast consumption for children in the US from 1965–1991 . Am J Clin Nutr. 1998;67(4):748S–56S [DOI] [PubMed] [Google Scholar]
  • 28.Reddan J , Wahlstrom K , Reicks M. Children’s perceived benefits and barriers in relation to eating breakfast in schools with or without Universal School Breakfast . J Nutr Educ Behav. 2002;34(1):47–52 10.1016/S1499-4046(06)60226-1 [DOI] [PubMed] [Google Scholar]
  • 29.Bertéus Forslund H , Torgerson JS , Sjostrom L , Lindroos AK. Snacking frequency in relation to energy intake and food choices in obese men and women compared to a reference population . Int J Obes (Lond). 2005;29(6):711–9 10.1038/sj.ijo.0802950 [DOI] [PubMed] [Google Scholar]
  • 30.Jahns L , Siega-Riz AM , Popkin BM. The increasing prevalence of snacking among US children from 1977 to 1996 . J Pediatr. 2001;138(4):493–8 10.1067/mpd.2001.112162 [DOI] [PubMed] [Google Scholar]
  • 31.Phillips SM , Bandini JG , Naumova EN , Cyr H , Colclough S , Ditez WH , et al. . Energy-dense snack food intake in adolescence: Longitudinal relationship to weight and fatness . Obes Res. 2004;12(3):461–72 10.1038/oby.2004.52 [DOI] [PubMed] [Google Scholar]
  • 32.de Graaf C Effects of snacks on energy intake: an evolutionary perspective . Appetite. 2006;47(1):18–23 10.1016/j.appet.2006.02.007 [DOI] [PubMed] [Google Scholar]
  • 33.Waller SM , Vander Wal JS , Klurfeld DM , McBurney MI , Cho S , Bijlani S , et al. . Evening ready-to-eat cereal consumption contributes to weight management . J Am Coll Nutr. 2004;23(4):316–21 [DOI] [PubMed] [Google Scholar]
  • 34.Kautiainen S , Koivusilta L , Lintonen T , Virtanen SM , Rimpela A. Use of information and communication technology and prevalence of overweight and obesity among adolescents . Int J Obes (Lond). 2005;29(8):925–33 10.1038/sj.ijo.0802994 [DOI] [PubMed] [Google Scholar]
  • 35.Rey-López JP , Vicente-Rodríguez G , Biosca M , Moreno LA. Sedentary behaviour and obesity development in children and adolescents . Nutr Metab Cardiovasc Dis. 2008;18(3):242–51 10.1016/j.numecd.2007.07.008 [DOI] [PubMed] [Google Scholar]
  • 36.Bercedo Sanz A , Redondo Figuero C , Pelayo Alonso R , Gomez Del Rio Z , Hernandez Herrero M , Cadenas Gonzalez N. Mass media consumption in adolescence . An Pediatr (Barc). 2005;63(6):516–25 [DOI] [PubMed] [Google Scholar]
  • 37.Lanningham-Foster L , Jensen TB , Foster RC , Redmond AB , Walker BA , Heinz D , et al. . Energy expenditure of sedentary screen time compared with active screen time for children . Pediatrics. 2006;118(6):e1831–35 10.1542/peds.2006-1087 [DOI] [PubMed] [Google Scholar]
  • 38.Eisenmann JC , Ekkekakis P , Holmes M. Sleep duration and overweight among Australian children and adolescents . Acta Paediatr. 2006;95(8):956–63 10.1080/08035250600731965 [DOI] [PubMed] [Google Scholar]
  • 39.Nixon GM , Thompson JM , Han DY , Becroft DM , Clark PM , Robinson E , et al. . Short sleep duration in middle childhood: risk factors and consequences . Sleep. 2008;31(1):71–8 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40.Knutson KL Sex differences in the association between sleep and body mass index in adolescents . J Pediatr. 2005;147(6):830–4 10.1016/j.jpeds.2005.07.019 [DOI] [PubMed] [Google Scholar]
  • 41.Tanner J. Growth at adolescence. 2nd ed. Springfield Ill: Charles C. Thomas;1962. [Google Scholar]
  • 42.Roche A, Sun S. Human growth: assessment and interpretation. Cambridge University Press: Cambridge; 2003. [Google Scholar]
  • 43.Ellison P. Puberty. In: Cameron N, ed. Human growth and development. Academic Press: Amsterdam; 2002. pp. 65–84. [Google Scholar]

Articles from Journal of Epidemiology are provided here courtesy of Japan Epidemiological Association

RESOURCES