BMI from 3 6 y of age is predicted by TV viewing and physical activity, not diet

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1 (2005) 29, & 2005 Nature Publishing Group All rights reserved /05 $ PEDIATRIC HIGHLIGHT BMI from 3 6 y of age is predicted by TV viewing and physical activity, not diet R Jago 1 *, T Baranowski 1, JC Baranowski 1, D Thompson 1 and KA Greaves 2 1 Children s Nutrition Research Center, Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA; and 2 The Solae Company, PO BOX 88940, St Louis, MO, USA OBJECTIVE: To investigate whether, diet, physical activity, sedentary behavior or television (TV) viewing predicted body mass index (BMI) among 3 7-y-old children. DESIGN: A triethnic cohort of 3 4-y-old children was followed for 3 y from 1986 to MEASUREMENTS: BMI was assessed at the beginning and end of each measurement year. Heart rate monitoring and observation were used to assess physical activity. Diet (calories, % calories from fat and carbohydrate), sedentary behavior and TV viewing were assessed by direct observation in each year. A repeated measures regression analysis with year as a factor and BMI at the end of each year as dependent variables was run. Nonsignificant variables were removed in a stepwise backward deletion process and significant interactions graphed. RESULTS: The interactions between minutes of TV viewing per hour and study year and minutes of physical activity per hour and study year were significant (Po0.05). There were also significant main effects for TV viewing, physical activity and BMI from the beginning of the study. The model accounted for 65% of the variance in BMI across the three study years. Plotting the significant interactions demonstrated that physical activity was positively associated with BMI in year 1, and negatively associated in years 2 and 3 with a stronger negative relationship in year 3 than 2. TV viewing became positively associated with BMI during the third study year. CONCLUSION: Physical activity and TV viewing were the only significant predictors (other than baseline BMI) of BMI among a triethnic cohort of 3 4-y-old children followed for 3 y with both physical activity (negatively associated) and TV viewing (positively associated) becoming stronger predictors as the children aged. It appears that 6 or 7 y is a critical age when TV viewing and physical activity may affect BMI. Therefore, focusing on reducing time spent watching television and increasing time spent in physical activity may be successful means of preventing obesity among this age group. (2005) 29, doi: /sj.ijo Keywords: children; calories; dietary fat *Correspondence: Dr R Jago, Department of Exercise and Health Sciences, Centre for Sport, Exercise and Health, University of Bristol, Tyndall Avenue, Bristol BS8 1TP, UK. russ.jago@gmail.com Received 29 September 2004; revised 8 February 2005; accepted 22 March 2005 Introduction Childhood obesity is increasing in the US with 15% of American children now being characterized as overweight (body mass index (BMI) Z95th percentile). 1 Obesity has been found to track from childhood to adulthood. 2 Since adult obesity is associated with increased risk of a number of diseases including type 2 diabetes, 3 many forms of cancer 4 7 and cardiovascular disease, 8 preventing childhood obesity could significantly impact adult quality of life. Obesity results from an energy imbalance whereby caloric consumption exceeds energy expenditure. 9 Dietary factors including total caloric intake and percent calories consumed from fat have been associated with increased adiposity among children. 10 Physical activity, the malleable component of energy expenditure, 9,11 has been associated with decreased adiposity among children and adolescents. 12 Sedentary behavior 13 and time spent watching TV, the most studied form of sedentary behavior, have been associated with increased adiposity. Since TV viewing has been associated with unhealthful dietary behaviors, such as increased consumption of soda, fried foods and snacks, 17 the relationship between TV viewing and increased adiposity could be a function of poor dietary choices while watching television. Although diet, physical activity and sedentary behaviors have independently been associated with adiposity among children, the relative importance of each behavior is unclear.

2 558 There is also a lack of research examining these associations among young children and whether these changes occur in the relationship as children develop. The possible role of ethnicity and gender on these relationships has also not been elucidated. Therefore, the aim of this paper is to examine whether physical activity, TV viewing, other sedentary behaviors and dietary factors predict BMI among a triethnic cohort of 3 4-y-old children followed over a 3-y period. Methods Data were collected as part of the Texas site of the Studies of Child Activity and Nutrition (SCAN) Program, a National Heart, Lung and Blood Institute funded multicenter study that examined the development of cardiovascular risk factors and associated behaviors in families of young children. 18,19 Data were collected between the summers of 1986 and While the data were collected over 15 y ago, there has been no significant change in the measurement techniques for the behaviors examined in this paper. Using data from early in the obesity epidemic also provides insights into how the disease has developed in the US. Furthermore, there is a lack of studies that have conducted simultaneous assessments of diet, physical activity and sedentary behaviors among young children. This paper addresses these limitations. Various methods, including newspaper advertisements, fliers, and word of mouth were used to recruit families. 20 Parents and their 3 4-y-old children were enrolled in year one and followed for 3 years, with only one child per family enrolled. Data for each of the three observation years are presented here. Participant s age, gender and ethnicity were obtained by maternal self-report. The University of Texas Medical Branch at Galveston s Institutional Review Board approved the study and written informed consent was obtained for all participants. Physiological and anthropometric assessments Height and weight were measured at baseline and at the end of each study year to the nearest centimeter and 0.1 kg using a Prospective Enterprises stadiometer and Detecto balancebeam scale following a standard protocol. 21 This process was repeated three times and the mean of the three recordings was used in all analyses. Each participant s BMI(kg/m 2 ) was then calculated for baseline and the end of each study year (BMI-base, BMI-Y1, BMI-Y2, BMI-Y3). Heart rate monitoring of physical activity Heart rate monitoring was used to assess the participant s physical activity. Children s heart rates were assessed on a minute-by-minute basis using heart rate telemetry. On an appointment basis, a research technician arrived at each child s home at approximately 0700 hours. A Quantum XL telemetry heart rate monitor (AMF Co., Jefferson, Iowa), preprogrammed to record for the entire day, was attached to each child s chest and later removed by a technician at approximately 0700 hours. Previous analyses have shown that this procedure provides a reliable assessment of children s physical activity. 22 Four days of monitoring per year were attempted during observation years 1 and 2; and 3 days were attempted during observation year 3. Acceptable heart rate values were between 50 and 220 bpm; the 4.0% of values outside this range were treated as outliers. A valid day consisted of at least 504 min (70%) of usable heart rate values. The average number of minutes that participants spent with mean heart rates 4140 bpm/h was interpreted as the number of minutes engaged in moderate to vigorous intensity physical activity 23 and will henceforth be referred to as minutes of heart rate monitored physical activity per hour. Observation of sedentary behavior and TV watching The Children s Activity Rating Scale, 24 a five-level observational rating system designed to record minute-by-minute physical activity in situations encompassing a variety of activities and intensities, was used to record the child s sedentary behavior. Level one was categorized as stationary/ nonmoving; level two was stationary/limb movement but not trunk movement; level three was translocation/slow walk; level four was translocation/fast walk and level five was translocation/running. 24,25 Each child was observed for approximately 6 12 h per day at the same time that the heart rate values were measured. Observers recorded the activity level at the start of each minute and then recorded any subsequent activity level changes during that minute. Each activity level could not be coded more than once during each minute. Minutes in which only levels 1 or 2 were observed, and not levels 3, 4 or 5 were coded as minutes of sedentary behavior. In addition to the CARS assessment, observers recorded whether the child was watching television during each minute of observation 26 (not just whether the TV was on, but whether the child was paying attention to the television). Diet Dietary consumption was recorded on the same days as physical activity and TV viewing by observers using methods that have previously been reported. 27 Briefly, trained teams of observers recorded participant s dietary consumption. Observers followed each child wherever he or she went (home, day care, school, etc.). All foods eaten by the child, nutrient-related characteristics of purchase and preparation and portion size consumed were recorded throughout the observation period. The observer also questioned the food preparer about ingredients and preparation practices as necessary. Food descriptions were entered onto 24-h recall forms and submitted to the Nutrition Coding Center (NCC) for nutrient analysis using the Nutrient Data System (NDS)

3 software. 28 Mean daily caloric intake, percent calories from fat, protein and carbohydrate was then calculated across the observation days in each year. Statistics To account for differences in length of observation per day, the average minutes of physical activity, TV viewing and sedentary behavior were calculated per hour. Descriptive statistics including means and standard deviations were calculated for all variables. Repeated measures analyses of variance (ANOVA) were used to test for differences across the 3 years. Significant ANOVA tests were examined using paired t-tests. To assess the stability across days of observation of the physical activity measures within each study year, one way random effect intraclass correlations were conducted on minutes of heart rate monitored physical activity per hour, minutes of observed physical activity per hour, TV viewing and sedentary behavior. To assess relationships among variables, Pearson correlations were conducted among all variables for each study year. A repeated measures regression analysis with year as a factor and BMI in each year as the dependent variable was then run. Behaviors (TV viewing, sedentary behavior, physical activity, diet variables), demographics (ethnicity and gender), BMI from the beginning of the study and interaction terms for variables differing by year (TV viewing, physical activity, sedentary behavior) were included as independent variables. Since this was an exploratory analyses, nonsignificant behaviors and interaction terms were removed in a step-wise backward deletion process. Significant interaction terms were graphed. Results Descriptive statistics for all variables are shown for each study year in Table 1. The participants were an average of 4.4 y old in the first year of the study and 6 y old in year three of the study. There were approximately 2.5 days of observation per year in each of the three study years. The participants were approximately evenly divided between the two genders with 47 49% being male. The sample was triethnic, 37% Anglo-American, 37% African American and 26% Hispanic. The percent of participants at risk of overweight (BMI 485th percentile for age and gender) increased from 10% in year 1 to 15% in year 3, with the percent overweight (BMI 495th percentile for age and gender) also increasing from 6% in year 1 to 10% in year 3. There were significant intraclass correlations across days for minutes spent watching TV per hour in year 1 (r ¼ 0.37, P ¼ 0.007), year 2 (r ¼ 0.56, Po0.001) and year 3 (r ¼ 0.35, P ¼ 0.005).There were significant intraclass correlations across days for minutes of heart rate monitored physical activity per hour in year 1 (r ¼ 0.42, Po0.001), year 2 (r ¼ 0.34, P ¼ 0.03) and year 3 (r ¼ 0.59, P ¼ 0.024). There were significant intraclass correlations across days for minutes of sedentary behavior in year 1 (r ¼ 0.65, Po0.001), year 2 (r ¼ 0.48, Po0.001) and year 3 (r ¼ 0.30, P ¼ 0.04). Repeated measures analysis of variance revealed a significant difference in minutes of TV viewing per hour across the 559 Table 1 Descriptive statistics (mean and s.d.) for minutes of TV per hour (TV/H), minutes of heart rate monitored physical activity per hour (HR PA/H), BMI (end of year assessment), minutes of sedentary behavior per hour (Sed/H), calories (Cals), % calories from fat (% Cals Fat) and % calories from carbohydrate (% Cals Carbs), age, gender and ethnicity in each study year Year 1 Year 2 Year 3 Mean s.d. N Mean s.d. N Mean s.d. N Days of observation TV/H*,a,b HR PA/H*,a,b BMI*, a,b,c % At risk of overweight d 10 NA NA NA 133 % Overweight e 6 NA NA NA 133 Sed/H*,a,c Cals % Cals Fat % Cals Carbs Age (y) Gender (% female) 51 NA NA NA 138 Ethnicity (% African American) 37 NA NA NA 138 Anglo-American (%) 37 NA NA NA 138 Hispanic (%) 26 NA NA NA 138 *Repeated measures analysis of variance significant (Po0.05) difference across the three study years. a Post hoc testing (t-test) significant difference (Po0.05) between years 1 and 3. b Post hoc testing (t-test) significant difference (Po0.05) between years 2 and 3. c Post hoc testing (t-test) significant difference (Po0.05) between years 1 and 2. d % Participants with BMI above the 85th percentile for gender and age according to CDC criteria. e % Participants with BMI above the 95th percentile for gender and age according to CDC criteria.

4 560 3 y (F (2,107) ¼ 4.24, P ¼ 0.017). Post hoc testing using paired t-tests yielded significant differences between years 1 and 3 (t ¼ 2.70, P ¼ 0.008), and years 2 and 3 (t ¼ 2.38, P ¼ 0.019). There was a significant difference in minutes of heart rate monitored physical activity per hour across the 3 years (F (2, 96) ¼ 5.89, P ¼ 0.004). Paired t-tests yielded significant differences between years 1 and 3 (t ¼ 3.10, P ¼ 0.002) and years 2 year 3 (t ¼ 2.15, P ¼ 0.034). There was a significant difference in BMI across the 3 years (F(2, 107) ¼ 220.1, Po0.001). Paired t-tests yielded significant differences between years 1 and 2 (t ¼ 2.60, P ¼ 0.011), years 1 and 3 (t ¼ 6.76, Po0.001) and years 2 and 3 (t ¼ 6.98, Po0.001). There was a significant difference in sedentary minutes across the 3 years (F (2,107) ¼ 108.9, Po0.001). Paired t-test yielded significant differences between years 1 and 2 (t ¼ 14.98, p4.001) and years 1 and 3 (t ¼ 14.37, Po0.001). Correlations among variables are shown for each study year in Table 2. Minutes of sedentary behavior per hour were negatively associated with percent calories from fat (r ¼ 0.192, Po0.05) and positively associated with percent calories from carbohydrates (r ¼ 0.229, Po0.05) in year 1. Percent calories from fat were negatively associated with percent calories from carbohydrate (r ¼ 0.885, Po0.001). Minutes of TV viewing per hour in year 2 were negatively associated with minutes of heart rate monitored physical activity per hour (r ¼ 0.243, Po0.05) and positively associated with minutes of sedentary behavior per hour (r ¼ 0.269, Po0.01). Minutes of heart rate monitored physical activity per hour were negatively associated with minutes of sedentary behavior per hour (r ¼ 0.268, Po0.05) and percent calories from fat (r ¼ 0.170, Po0.05). Percent calories from fat were negatively associated with percent calories from carbohydrate (r ¼ 0.888, Po0.001) (Table 2). Minutes of TV per hour in year 3 were negatively associated with minutes of heart rate monitored physical activity per hour (r ¼ 0.197, Po0.05) and positively associated with minutes of sedentary behavior per hour (r ¼ 0.407, Po0.01) in year 3. Minutes of heart rate monitored physical activity per hour were negatively associated with minutes of sedentary behavior per hour (r ¼ 0.317, Po0.01) and positively associated with calories (r ¼ 0.282, Po0.01). Minutes of sedentary behavior per hour were negatively associated with calories (r ¼ 0.233, Po0.01). BMI from the end of year 3 was positively associated with calories (r ¼ 0.196, Po0.05). Percent calories from fat were negatively associated with percent calories from carbohydrate (r ¼ 0.885, Po0.001) (Table 2). The results of the repeated measures regression model predicting BMI across all 3 years are shown in Table 3. The interactions between minutes of TV viewing per hour by year interaction terms were significant for year 1 (std. Table 2 Correlations among minutes of TV viewing per hour (TV/H), minutes of heart rate monitored physical activity per hour (HR PA/H), minutes of sedentary behavior per hour (Sed/H), BMI (from end of study year), calories (Cals), percent calories from fat (% Cals Fat ) and % calories from carbohydrate (% Cals Carbs) separately for years 1, 2 and 3 Year 1 TV/H HR PA/H Sed/H BMI Cals % Cals Fat % Cals Carbs TV/H 1 HR PA/H Sed/H BMIFY Cals 0.221* % Cals Fat * % Cals Carbs * *** 1 Year 2 TV/H 1 HR PA/H 0.243* 1 Sed/H 0.269** 0.268* 1 BMIFY Cals % Cals Fat * % Cals Carbs *** 1 Year 3 TV/H 1 HR PA/H 0.197* 1 Sed/H 0.407** 0.317** 1 BMIFY * Cals ** 0.233** 0.196* 1 % Cals Fat % Cals Carbs *** 1 *Po0.05, **Po0.01, ***Po Bold values are Po0.05.

5 Table 3 Repeated measures regression analyses (year as a factor) with, behaviors, demographics and interaction terms predicting BMI across all 3 years 561 Dependent variable Independent Variable Beta s.e. T-value Std. Beta Sig. BMI TV/H o0.001 HR PA/H BMI base o0.001 Gender (ref. female) Ethnicity (ref. Anglo) Hispanic African-American Year (ref. year 3) Year Year TV/H * Year (ref. year 3) TV/H * Year TV/H * year HR PA/H * year (ref. year 3) HR PA/H * year HR PA/H * year R 2 ¼ 0.65 Nonsignificant variables and interaction terms were deleted. Bold values are Po BMI with remaining predictors held constant* Year 1 Year 2 Year 3 Figure Minutes of physical activity per hour Physical activity and predicted BMI for each year. * (Predicted BMI with TV viewing, BMI base, gender and ethnicity held constant at mean values). Beta ¼ 0.14, P ¼ 0.017) and year 2 (std. Beta ¼ 0.15, P ¼ 0.009) when contrasted with year 3. The interaction between minutes of physical activity per hour by year interaction terms was significant for year 1 (std. Beta ¼ 0.19, P ¼ 0.002) and was close to significance for year 2 (std. Beta ¼ 0.11, P ¼ 0.054) when contrasted with year 3. Figure 1 highlights that while physical activity was positively associated with BMI in year 1, it was negatively associated in years 2 and 3 with a stronger negative relationship in year 3 than 2. There were also significant main effects for TV viewing (std. Beta ¼ 0.22, Po0.001), physical activity (std. Beta ¼ 0.20, P ¼ 0.003), and BMI from the beginning of the study (std. Beta ¼ 0.65, Po0.001). The model accounted for 65% of the variance in BMI across the three study years. Figure 2 highlights that the relationship between TV viewing and BMI becomes significant in year 3 where increased TV viewing is clearly associated with increased BMI. Discussion The results presented here indicate that the interactions between study year and both TV viewing and physical activity were the only variables other than the main effects for TV viewing, physical activity and BMI from the beginning of the study that predicted BMI among 3 7-y-old children across three study years. This suggests substantial developmental differences, with relationships emerging at about 6 or 7 y of age. As far as we are aware this is the first study to document such developmental differences in these relationships with BMI. The relationship between TV viewing and BMI was a strong positive association in year 3. Although some previous studies have reported associations between TV viewing and increased adiposity among both children and adolescents, 32,33 other investigations have found either no association 26,34 or inconsistent associations. 35 Further,

6 BMI with remaining predictors held constant # Year 1 Year 2 Year 3 Figure Minutes TV viewing per hour TV viewing and predicted BMI for each year. # (Predicted BMI with physical activity, BMI base, gender and ethnicity held constant at mean values). although a recent meta-analysis 36 of 39 articles concluded that there was a statistically significant, but small relationship between TV and adiposity among adolescents and children, it was also concluded that this relationship was too small to be clinically relevant. Most (94%) of those articles, however, were based on self-reported estimates of TV watching. Furthermore, the observational studies, 26,34 which employed just bivariate correlational methods, found no significant (Po0.05) association between TV viewing and adiposity at and y of age which is similar to the findings reported here. Physical activity, diet and sedentary behavior were not included in those analyses. The analyses reported in this paper, therefore, suggest that television viewing is associated with increased adiposity among 6 7-yold children especially after accounting for other contributing factors such as baseline BMI, physical activity and diet. The strength of the present findings include the objective (non-self-report) nature of the variables and the longitudinal nature of the design. Thus, reducing television viewing among young children at an early age may help to prevent the development of obesity. Although minutes of heart rate monitored physical activity were positively associated with BMI in the first year of the study, there was an inverse relationship in years 2 and 3 with the relationship becoming stronger in year 3 than in year 2. Previous cross-sectional 12,37 and cohort 38 research showed that increased physical activity was associated with decreased BMI among children and adolescents. The findings of this study suggest that this relationship may vary during the developmental process becoming more significant as children age. This would suggest that focusing on preventing the known declines in childhood physical activity 39,40 at 4 y of age would help to curb the current obesity epidemic. Dietary factors were not associated with BMI across the three study years. Previous studies have reported that dietary fat consumption was associated with increased BMI among children and adolescents However, two studies conducted among preschool children reported no relationship between the participants dietary fat intake and their levels of BMI. 45,46 This may suggest that the young age of the participants in this study limited our ability to detect an association between dietary fat intake and BMI. As it has been reported that the sum of skinfolds, and not BMI, was associated with dietary fat among a cohort of Australian children, the lack of an association could also be a function of the imprecision of BMI. 47 Further research examining the relationship among dietary patterns and multiple indicators of BMI in preschool children is required. TV watching but not sedentary behavior was a significant predictor of BMI across the three study years. Sedentary behavior has been weakly associated with BMI in previous studies. 36 However, as the term sedentary behavior usually includes TV viewing 36 (time spent watching TV was also included in sedentary behavior in this study), it is possible that relationships detected in other investigations could be largely attributable to television viewing. Alternatively, it could be that the relationship between sedentary behavior and BMI does not become significant until later in childhood when patterns of behavior may change. Partial support for this hypothesis can be drawn from the data presented in Table 1 which showed that minutes of sedentary behavior per hour were significantly greater in year one than in years two and three (52.9 vs 37.1 and 36.1). This dramatic change could reflect changes in daily activity patterns that occurred when the participants began to attend preschool or another day-care facility. Further changes that may occur during childhood could alter the association between sedentary behavior and BMI. Future research should explore this issue. Correlational analyses highlighted that TV viewing was positively associated with sedentary behavior and negatively associated with physical activity in years 2 and 3. This suggests that reducing the time spent watching television may result in increased physical activity. Moreover, there was

7 no significant correlation between time spent watching television and the percentage of calories consumed from fat in any of the three observation years. This is contrast to a recent study in which it was reported that TV viewing was associated with unhealthful dietary behaviors such as increased consumption of soda, fried foods and snacks. 17 This may suggest that the relationship changes during the developmental process becoming stronger as children age. This conclusion is supported by another study that reported an inverse association between TV viewing and fruit and vegetable consumption among adolescents 48 and collectively the three studies suggest that further research on TV watching and diet among young children is warranted. Strengths and limitations The major strengths of this study were the ability to assess the relative influence of diet, physical activity, sedentary behavior and TV viewing on the BMI of young children and do this over a period of 3 years. A further strength was the young age of the triethnic cohort, which enabled an exploration of the influence of behaviors on BMI prior to the onset of puberty. It is important to highlight, however, that this sample is unlikely to represent the behaviors of current children and therefore the results may not be generalizable. Although significant (all Po0.05), the intraclass correlations conducted on minutes of physical activity, sedentary behavior and TV viewing within each study year were moderate (r ¼ 0.30 to 0.65). This suggests that there was considerable day to day variability among these measures and indicates that additional days of monitoring would be required to provide an accurate assessment of the participants habitual patterns of behavior. This is in agreement with the work of Trost et al 49 who reported that between 4 and 5 days of monitoring were required to attain a reliability of 0.80 among children. It is possible that the lack of variability in the dietary measures across the 3 years could be a factor as to why the dietary variables were not associated with BMI. As the results of this study suggest that TV viewing and physical activity patterns change as children age, similar changes may be evident in dietary variables at a point later in childhood. Examining the influence of behaviors on participants BMI over a longer period of time would facilitate a greater understanding of the factors that influence children s BMI through the developmental process. Conclusion TV viewing and physical activity predicted BMI across the three study years, but the nature of the relationships changed during the study period with both TV viewing and physical activity becoming more important as the children grew older. BMI from the beginning of the study was the strongest predictor of BMI at the end of the study. 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