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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
 
Int J Obes (Lond). Author manuscript; available in PMC 2014 January 1.
Published in final edited form as:
PMCID: PMC3628946
NIHMSID: NIHMS425331

Association between objectively measured sedentary behavior and body mass index in preschool children

Wonwoo Byun, PhD,1 Jihong Liu, ScD,2 and Russell R. Pate, PhD1

Abstract

OBJECTIVE

To determine the association between accelerometry-derived sedentary behavior and body mass index (BMI) z-score in preschool children and to determine whether the association changed when applying three different accelerometry cutpoints for sedentary behavior.

DESIGN AND SUBJECTS

Cross-sectional design. Data came from two completed studies: Children’s Activity and Movement in Preschool Study (CHAMPS) and the Environmental Determinants of Physical Activity in Preschool Children (EDPAPC) study. Children ages 3 to 5 with complete data on sedentary behavior, BMI z-score, physical activity, and other covariates were included in the analyses (N = 263 in CHAMPS and N = 155 in EDPAPC). Accelerometry data were summarized as time spent in sedentary behavior (min/hr) using three different cutpoints developed specifically for preschool children (< 37.5, <200, and <373 counts/15 seconds). Linear mixed regression models were used to determine the association between time spent in sedentary behavior and BMI z-score; age, gender, race, parental education, preschools, and moderate-to-vigorous physical activity (MVPA) were included as covariates.

RESULTS

In both CHAMPS and EDPAPC study, no independent association between time spent in sedentary behavior and BMI z-score was observed after adjusting for MVPA. The observed null association between sedentary behavior and BMI z-score was maintained even with different sedentary behavior cutpoints.

CONCLUSIONS

Regardless of cutpoints used, accelerometry-derived sedentary behavior was not independently associated with BMI z-score in two independent samples of preschool children. Longitudinal studies addressing this research question are needed.

Keywords: Accelerometer, preschool, sedentary behavior, BMI

INTRODUCTION

The prevalence of pediatric obesity has increased dramatically in recent decades,1, 2 and this trend also has been observed in preschool children (ages 3 to 5 years).3 Reversing the childhood obesity epidemic has become urgent public health priorities, because childhood and adult obesity are strongly linked.4 In considering modifiable risk factors associated with childhood obesity, it has been hypothesized that sedentary behavior is independently associated with the increased risk of childhood obesity.5, 6

Cross-sectional and longitudinal studies have reported that sedentary behavior is a risk factor for overweight and obesity in preschool children.711 In those studies, however, sedentary behavior was measured using proxy reports (i.e., parent-reported time spent watching TV and playing video games), and the potential influence of children’s physical activity on the association between sedentary behavior and obesity was not taken into account. Studies that have examined the relationship between objectively-measured sedentary behavior and obesity in preschool children are very limited,12 and no previous study has investigated the association between accelerometry-derived sedentary behavior and obesity in preschool children, adjusting for time spent in moderate-to-vigorous physical activity (MVPA).

Accelerometry is a known objective measure of sedentary behavior in preschool children.1317 To date, studies have used several accelerometry cutpoints to estimate sedentary behavior in preschool-age children; these include <37.5 counts/15sec,18 <200 counts/15sec,18 <373 counts/15sec,19 and <1100 counts/60sec.20 Depending on the cutpoints used, the estimates of accelerometry-derived time spent in sedentary behavior can vary considerably (e.g., 343.2 min/day to 617.6 min/day).19, 21 Therefore, it is possible that the association between sedentary behavior and health outcomes of interest could be influenced by the cutpoint applied.

The primary purpose of this study was to determine the independent association between accelerometry-derived sedentary behavior and body mass index (BMI) z-score in a cross-sectional sample of preschool children enrolled in two existing studies. A secondary purpose was to determine whether the association was similar when three different accelerometry cutpoints for sedentary behavior were applied.

MATERIALS AND METHODS

Study Design

The aims of this study were addressed using two existing cross-sectional datasets, The Children’s Activity and Movement in Preschool Study (CHAMPS) and the Environmental Determinants of Physical Activity in Preschool Children (EDPAPC) study. Full details regarding the design of each study are reported elsewhere.22, 23 In brief, both CHAMPS and the EDPAPC study collected activity data in preschool children over a two-week period. In CHAMPS, children’s total-day activity (in-school and out-of-school) was measured, but only in-school activity data were collected in the EDPAPC study. It has been suggested that at least 2 days or 6 days of accelerometry monitoring are required to reliably measure (intraclass correlations ≥ 0.80) school-day or total-day sedentary behavior in preschool children, respectively.24 For the analyses in the current study, we included children who had at least 3 days of in-school sedentary behavior data in the EDPAPC study, and at least 6 days of total-day sedentary behavior data in CHAMPS.

Participants

The participants in this study were preschool children, aged 3 to 5 years, who were enrolled in the CHAMPS22 and EDPAPC study.23 In both studies, all preschools with an enrollment of 60 or more children in the greater Columbia, South Carolina area were identified. The preschools were stratified into one of three types: Head Start, private, and religious. After random selection from each stratum (school type), 22 preschools and 9 preschools were recruited in CHAMPS and EDPAPC study respectively. The number of participants per preschool ranged from 14 to 33 in CHAMPS, and from 22 to 30 in EDPAPC. The participants in both studies were from diverse socio-demographic backgrounds, and the race/ethnicity distribution of participants reflected that of the population in the greater Columbia area.25 A total of 263 children (51% girls, 51% Black) from CHAMPS, and 155 children (49% girls, 55% Black) from EDPAPC were available for the present analyses after excluding children with missing data on the study variables (≈38% in CHAMPS and ≈41% in EDPAPC). The distributions of age, gender, race, BMI, and parent education level were not different between children who were included and excluded. Written informed consent was obtained from children’s parents or guardians prior to collection of data. Both studies were approved by the Institutional Review Board at the University of South Carolina.

Assessment of sedentary behavior

In both studies, sedentary behavior was measured using ActiGraph accelerometers (ActiGraph model 7164, Shalimar, FL). In order to capture the spontaneous activities of 3- to 5-year-old children, the accelerometers were initialized to save data in 15-second intervals (epochs). Each child was instructed to wear the accelerometer on an elastic belt on the right hip. In CHAMPS, participants wore the accelerometer for the total day (during and after school hours). The parents of CHAMPS participants received information about the accelerometer, and instructions on how their child should wear the monitor over a two-week period. Unlike CHAMPS, the participants in the EDPAPC study wore the accelerometer for the duration of his/her stay at the preschool (at least six hours) during a two-week period. Accelerometers were placed when children arrived at preschool and were removed right before children left for the day. All the preschools included in this study scheduled a nap during each day (≈ 1 hour), and children wore accelerometers during nap time. Because all children were required to be sedentary during this period, nap time was included in the total wear time.

Accelerometry data reduction

The accelerometer count data were reduced using three different activity intensity cutpoints developed specifically for 3- to 5-year-old children. The sedentary behavior cutpoints used were < 37.5 counts/15 sec,18 <200 counts/15 sec,18 and <373 counts/15 sec.19 The cutpoint for MVPA was ≥420 counts/15sec.18 Using each child’s wear time as the divisor, cumulative time spent in sedentary behavior and MVPA was averaged on an hourly basis (min/hr) to take into account differences in the monitoring time of children on a given day. Sixty-minutes of consecutive zeros was considered as non-wear time. In both CHAMPS and EDPAPC, days that children were absent from preschool and on which total wear time was ≥18 hours (i.e., monitor malfunction) or <6 hours were excluded from the analysis because those days do not represent typical days.

Demographic characteristics

In both CHAMPS and EDPAPC, children’s age, gender, race/ethnicity, and socioeconomic status (parental education level) were reported by a parent or guardian using a self-administered parent survey.

Anthropometry and BMI z-score

In both studies, weight was measured to the nearest 0.1 kg using an electronic scale, and height was measured to the nearest 1 mm using a stadiometer, after the child removed shoes and outer clothing. The average of two measurements was used to determine height and weight. Body Mass Index (BMI) was calculated as weight divided by height squared (kg/m2). BMI z-score was calculated by assessing the deviation of each child’s BMI value from the population mean BMI values reported in the CDC growth charts.26

Statistical analyses

Descriptive statistics for the participants were calculated, using means and standard deviations for continuous variables, and frequencies and percent for categorical variables. Simple t-tests and Chi-square tests of independence were used to examine differences in age, gender, race, parent education level, BMI, BMI z-score, and accelerometry wear time between participants in CHAMPS and EDPAPC. Gender differences in the amount of time spent in sedentary behavior were examined using independent sample t-tests.

Mixed linear regressions (PROC MIXED procedure in SAS) were used to determine the association between accelerometry-derived sedentary behavior and BMI z-score. BMI z-score was regressed on time spent in sedentary behavior (min/hr) for each of the three sedentary behavior estimates. To take into account the correlation among children from the same preschool, the models included preschool as a random effect. Socio-demographic factors such as age, gender, race, and parent education level were included as covariates in the mixed models (Model 1). The levels of MVPA (min/hr) were additionally adjusted to fully determine the independent association between sedentary behavior and BMI z-score in mixed models (Model 2) due to significant relationships of MVPA with adiposity in preschoolers.2729 Interactions terms between sedentary behavior and socio-demographic factors also were included in mixed models (Model 1 and 2). If there was statistical evidence of interactions, we performed the stratified analyses to determine if the association between sedentary behavior and BMI z-score differed by these socio-demographic factors. All data were analyzed using SAS version 9.2 (SAS Institute, Cary, NC, USA).

RESULTS

Descriptive characteristics

As shown in Table 1, the gender and race characteristics of children were similar between CHAMPS and the EDPAPC study. BMI and BMI Z-score were slightly higher among the participants in CHAMPS compared to those in EDPAPC. The average number of days and hours that children wore the accelerometers were 7.5 days and 13.1 hrs/day in CHAMPS, and 7.5 days and 7.6 hrs/day in the EDPAPC study, respectively.

Table 1
Characteristics of Participants in CHAMPS and EDPAPC, Mean ± SD or Percent

Time spent in sedentary behavior

The estimated times spent in sedentary behavior using the three cutpoints are presented in Table 2. Depending upon the cutpoint used, the average time spent in sedentary behavior varied from 32 min/hr to 51min/hr in CHAMPS, and from 38 min/hr to 54 min/hr in the EDPAPC study. In both CHAMPS and the EDPAPC study, boys spent less time in sedentary behavior than girls.

Table 2
Time Spent in Accelerometry-derived Sedentary Behavior and MVPA According to Three Different Cutpoints (Mean ± SD)

Association between sedentary behavior and BMI z-score

The associations between sedentary behavior and BMI z-score in CHAMPS are presented in Table 3. Across three different cutpoints used, sedentary behavior was inversely associated with BMI z-score among CHAMPS participants after adjusting for age, gender, race, parent education level, and preschool (Model 1). However, this association was eliminated after additionally adjusting for levels of MVPA (Model 2). In the EDPAPC study, sedentary behavior was not associated with BMI z-score after adjusting for potential confounders (Table 3). We did not find any significant interaction indicating that the association between sedentary behavior and BMI z-score did not differ by these socio-demographic factors.

Table 3
Association Between Sedentary Behavior (min/hr) and BMI z-score in Preschool Children

DISCUSSION

The association between sedentary behavior and adiposity in the preschool population has not been studied extensively. In the current study, we investigated the association between objectively-measured sedentary behavior and BMI z-score in two independent samples of preschool children. We found that accelerometry-derived sedentary behavior was not independently associated with BMI z-score after adjusting for important confounders, including MVPA, in two samples of preschool children. These findings are of particular importance because some public health authorities have suggested that reducing sedentary behavior may be an important strategy for prevention of obesity in preschool children.30, 31 Within the limitations of a cross-sectional study, our findings indicate that sedentary behavior may not be an independent risk factor for obesity in preschool children.

Three large cross-sectional studies have examined the association between accelerometry-derived sedentary behavior and measures of adiposity in primary school-age children (ages 9 – 12 years).3234 In all three studies, no association was observed between sedentary behavior and adiposity, after adjusting for time spent in MVPA.3234 In addition, the largest cross-sectional analysis to date (N=20,871) reported that accelerometry-derived sedentary behavior was not associated with waist circumference in children and adolescents.35 To the best of our knowledge, only one study has examined the association between accelerometry-derived sedentary behavior and BMI z-score in preschool children.12 In that study, no significant correlation was found between sedentary behavior and BMI z-score. Collectively, based on those data and our findings, it does not appear that an independent association exists between accelerometer-derived sedentary behavior and adiposity in childhood.12, 3234

In contrast, accelerometry-derived sedentary behavior consistently has been associated with adiposity in adults, independent of time spent in MVPA.3638 A common biological mechanism used to explain the independent association in adults is that high sedentary behavior contributes to lower energy expenditure, which predisposes to excessive weight gain.39 It is likely that the same mechanism is operating in children.40 However, one explanation for an absence of a clear association between sedentary behavior and BMI z-score in young children could be the absolute level of sedentary behavior. On average, time spent in sedentary behavior is significantly lower in younger children, compared to older children and adults.35, 41 Although preschool children engage in a significant amount of time in sedentary behavior, the level of sedentary behavior may not be sufficient to reduce energy expenditure to the extent needed for an increase in BMI.

Another possible explanation for the absence of a significant association between sedentary behavior and adiposity may be the unique activity pattern of typical preschoolers. Preschoolers’ activity is intermittent and sporadic in nature,42, 43 and it is likely that frequent breaks occur in their sedentary behavior. Interestingly, studies have shown that more frequent breaks in sedentary time associate with lower BMI in adults, independent of the total time spent in sedentary behavior.38, 44 Therefore, we speculate that the lack of an association between sedentary behavior and BMI in our sample of preschool children could be due to the high frequency of breaks in sedentary behavior, independent of total sedentary behavior.

Future studies should consider the following issues to better understand the association between sedentary behavior and adiposity in preschool children. Preschool age is a period of fast physical growth, and the adiposity rebound complicates the association between sedentary behavior and adiposity further.4547 Although BMI is a good surrogate measure of adiposity in preschool children,48 it may not be sensitive enough to assess body fatness of young children. Changes in BMI during preschool age are likely due to both body fat and lean mass changes.49 Considering these issues, more precise measures of adiposity in preschool children are needed. Also, prospective studies that follow children throughout the period of adiposity rebound are needed to fully understand the relationship between sedentary behavior and BMI in preschool children.

A secondary aim of this study was to determine whether the association between accelerometry-derived sedentary behavior and BMI z-score was affected by applying different accelerometry cutpoints. The cutpoints used to define sedentary behavior in preschool children range from <26 counts/15sec50 to <1100 counts/60sec.20 We observed that the estimated times spent in sedentary behavior varied according to the cutpoints used. However, regardless of the cutpoint used, sedentary behavior was not independently associated with BMI z-score in our samples of preschool children. The results from this comprehensive approach indicate that our finding of no association between sedentary behavior and BMI z-score was not biased due to the selection of certain cutpoints.

This study had several strengths and limitations. Strengths include the use of accelerometry to quantify the amount of time spent in sedentary behavior. While other methods (e.g., parent reports and direct observation) measure sedentary behavior in preschool children, accelerometry provides an objective assessment and limits researcher burden.13, 18 The present study included two relatively large independent samples of preschool children from diverse social and demographic backgrounds. In addition, the children had good compliance with wearing the accelerometers. Accelerometry has limitations to discriminate between sitting and standing, and to capture upper body movement which may increase preschoolers’ energy expenditure level above that of sedentary. Another limitation is that the participants in this study were volunteers from preschools located in one geographic region, and the nature of the cross-sectional study design precludes establishing the causality of findings.

In conclusion, sedentary behavior was not independently associated with BMI z-score in large samples of preschool children. Longitudinal studies that account for the growth patterns of preschool children would advance our understanding of the association between sedentary behavior and adiposity in young children.

Acknowledgments

Supported by National Institute of Child Health and Human Development grants R01HD043125 and a grant from the Gerber Products Company. We thank all participants, parents, and preschools that participated in this investigation and Drs. Steven N. Blair and Michael Beets for editorial assistance in the preparation of the manuscript.

Footnotes

Disclosure: The National Institute for Child Health and Human Development grant R01HD043125 and a grant from the Gerber Products Company

CONFLICTS OF INTEREST

The authors declare no conflict of interest.

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