Accelerometer-Assessed Physical Activity and School Absenteeism Due to Illness or Injury Among Children and Adolescents: NHANES 2003 to 2006

Abstract

Introduction:

To examine the association between objectively measured moderate to vigorous physical activity (MVPA) and total physical activity with school absenteeism due to illness or injury among children and adolescents.

Design:

Cross-sectional study.

Setting:

National Health and Nutrition Examination Survey 2003 to 2006.

Participants:

A total of 1249 children (aged 6-11 years) and 1747 adolescents (aged 12-17 years).

Measures:

School absenteeism was categorized as no/minimal school absenteeism (0-8 missed school days in the past 12 months), moderate absenteeism (9-17 missed days), or severe absenteeism (18+ missed days). Physical activity was objectively measured via accelerometry.

Analysis:

Multinomial logistic regression.

Results:

Children in the most active quartile had 89% reduced odds of severe absenteeism relative to the least active quartile (odds ratio [OR]: 0.11; 0.95% confidence interval [CI]: 0.02-0.48); results were similar for MVPA. For adolescents, those in the most active quartile for MVPA had a 41% reduced odds of having moderate (vs no/minimal) absenteeism (OR = 0.59; 95% CI: 0.35-0.99). For children, a multiplicative interaction effect of MVPA and poverty level on severe absenteeism was observed (OR = 0.98, P = .02).

Conclusion:

Higher levels of physical activity were associated with lower odds of severe school absenteeism. Such an observation is important, as school absenteeism strongly contributes to academic performance. Particular attention for promoting physical activity and closely monitoring school absenteeism among youth below the poverty level may be warranted.

Keywords

academic performance epidemiology exercise NHANES

Introduction

Among children and adolescents, chronic school absenteeism detrimentally influences academic performance.^1,2 Predictors of absenteeism in America include weak student to teacher relationships, low socioeconomic status (SES), minority students, inadequate parental discipline, and cognitive disorders requiring special education.³ However, increased levels of physical activity may reduce depressive symptoms and increase self-efficacy,⁴ which may favorably impact academic performance. Exercise-associated improvements in various cognitive-related parameters⁵ provide suggestive evidence for a means through which physical activity may help to improve academic performance.⁶ A growing body of supporting literature indicates increased oxygen and blood flow to the brain improves memory and concentration.⁵ Physical activity may also indirectly influence academic performance via its potential influence on school absenteeism,⁷ among other factors. As an example, physical inactivity is associated with overweight and obesity,⁸ and overweight and obesity are associated with greater school absenteeism.⁹ Physical inactivity, coupled with increased television viewing time, is also associated with school absenteeism.⁷ Physical inactivity is heightened as a function of cumulative screen, video game, and TV time, while specific sedentary behaviors involving reading and completing homework do not exert the same detrimental effect on weight status and body composition.¹⁰ To date, only 1 study using a national sample of US children and adolescents has evaluated the association between physical activity and school absenteeism.⁷ A significant relationship was found between increased levels of screen time and physical inactivity on school absenteeism among children (not adolescents). An inverted U-shaped association was observed, meaning highly active and highly inactive adolescents experienced similar risks of absenteeism.⁷ Notably, this study employed a subjective assessment of children and adolescents’ physical activity. The purpose of this study was to complement the study by Hansen et al⁷ by employing an objective measure of physical activity (accelerometry); among children and adolescents in the 2003 to 2006 National Health and Nutrition Examination Survey (NHANES), here we examine the association between accelerometer-assessed physical activity and school absenteeism. Additionally, we also evaluate the potential interaction effects of physical activity and demographic characteristics (eg, poverty level) on school absenteeism. Such an exploration is warranted. For example, and as previously noted, low SES is associated with increased school absenteeism and physical inactivity among children.¹¹

Methods

Design

Data were used from the 2003 to 2006 NHANES. These NHANES cycles were evaluated as they are the only currently available NHANES cycles with accelerometry data. The NHANES employs a multistage, complex probability study design. Procedures were approved by the National Center for Health Statistics review board; consent was obtained prior to data collection. The primary variables of interest for the present study included physical activity and absenteeism rate (outcome).

Sample

Participants, across 15 different geographic regions in the United States, were interviewed in their home and subsequently evaluated in a mobile examination center. In the 2003 to 2006 NHANES, 5607 participants aged 6 to 17 years were enrolled. Among these, 3174 provided sufficient (described below) accelerometer data. Among these, 3118 had complete data on the outcome measure (absenteeism). Among these, 2996 had complete data on the study covariates (described below). Thus, our analytic sample included these 2996 participants; among these, 1249 were children (aged 6-11 years) and 1747 were adolescents (aged 12-17 years).

Measures

Measurement of absenteeism

Identical to Hansen et al,⁷ school absenteeism was assessed from the question, “During the past 12 months, that is, since (current month) of (last year), about how many days did (you/survey participant) miss school because of an illness or injury?” A parent or guardian proxy reported for children, while responses from adolescents were self-reported. The response scale for this item was the “number of days” of missed school, with the range in this sample being 0 to 120 days. Identical to Hansen et al,⁷ participants were categorized as no/minimal school absenteeism (0-8 missed school days in the past 12 months), moderate absenteeism (9-17 missed days), or severe absenteeism (18+ missed days). To our knowledge, the validity and reliability of this NHANES absenteeism variable have not been evaluated in a psychometric study. However, the study by Hansen et al did demonstrate an association between self-reported physical activity and this NHANES absenteeism variable, suggesting some evidence of construct validity for this item.

Measurement of physical activity

Objectively measured, free-living moderate to vigorous physical activity (MVPA) and total physical activity were evaluated herein using an ActiGraph 7164 accelerometer, which has been administered in childhood physical activity research with adequate reliability and validity.¹² Participants wore the monitor for up to 7 consecutive days. Only those with ≥4 days of ≥10 hours/day of monitored data were evaluated. Activity counts/minute ≥2020 were used to define MVPA,¹³ where counts represent vertical accelerations denoting intensity of physical activity per minute. Total physical activity is defined as activity counts/minute ≥100.¹⁴ Nonwear time was identified as ≥60 consecutive minutes of 0 activity counts, with allowance for 1 to 2 minutes of activity counts between 0 and 100.¹⁵ Notably, a number of comparison studies have evaluated ActiGraph accelerometry and have demonstrated evidence of both adequate levels of relative validity (eg, r = .77 when compared to oxygen uptake)¹⁶ and reliability (eg, ±68 counts/minute for interinstrument reliability).¹⁷

Covariates

Evaluated covariates included age (years; continuous), gender, race–ethnicity (Mexican American, non-Hispanic white, non-Hispanic black, and other), measured body mass index (kg/m²; continuous), and income-to-poverty ratio (range, 0-5).¹⁸ These covariates were selected based on previous research demonstrating their association with physical activity or school attendance.⁷

Age, gender, and race–ethnicity were evaluated via self-report. Body mass index was assessed from measured height and weight using standard anthropometric procedures. Socioeconomic status was assessed using the income-to-poverty ratio. Ranging from 0 to 5, income-to-poverty ratio was defined as the ratio of the family income to the federal poverty threshold. For example, an income-to-poverty ratio of 0.5 suggests that the family income is 50% below the poverty threshold.

Analysis

All statistical analyses were performed using procedures from sample survey data using Stata (version 12.0, College Station, Texas) to account for the complex survey design used in NHANES. To account for oversampling, nonresponse, noncoverage, and to provide nationally representative estimates, all analyses included the use of appropriate survey sample weights, clustering, and primary sampling units. A multinomial logistic regression analysis was used to examine the association between physical activity and school absenteeism (outcome variable). For the 3-level absenteeism variable, no/minimal absenteeism served as the referent group. Models were computed separately for children and adolescents and separately for MVPA and total physical activity. Multiplicative interaction analyses were computed by creating a cross-product term, and including it, along with the main effects and covariates, in the adjusted multinomial logistic regression model. As demonstrated in the Results section, sensitivity analyses evaluated these associations with physical activity expressed as continuous and categorical variables. Statistical significance was established as P < .05.

Results

Table 1 displays the study variable characteristics for the children and adolescent samples. For both children and adolescents, those with severe absenteeism were more likely to be female, had a lower SES, and engaged in less MVPA and total physical activity.

Table 1.

Study Variable (Weighted) Characteristics Among Children and Adolescents, 2003 to 2006 NHANES.^a,b,c

Variable	Children (n = 1249)			Adolescents (n = 1747)
	Absenteeism			Absenteeism
	Minimal	Moderate	Severe	Minimal	Moderate	Severe
n	1146	88	15	1579	120	48
Age, mean, years	8.5 (8.3-8.6)	8.7 (8.2-9.1)	8.7 (7.8-9.5)	14.4 (14.2-14.5)	14.2 (13.9-14.6)	14.4 (13.8-15.1)
BMI, mean, kg/m²	18.1 (17.8-18.4)	18.9 (17.4-20.4)	18.3 (16.3-20.3)	22.4 (21.9-22.9)	23.8 (22.2-25.3)	23.2 (20.7-25.7)
Gender: male, %	51.9	48.5	41.7	52.3	42.4	30.9
Race–ethnicity, %
Mexican American	14.1	5.2	1.3	11.3	6.4	7.7
Non-Hispanic white	57.1	80.0	88.8	63.2	73.7	69.7
Non-Hispanic black	15.0	9.3	9.9	14.0	12.2	19.1
Other	13.8	5.4	0	11.5	7.7	3.5
Poverty, mean	2.5 (2.3-2.8)	2.6 (2.1-3.0)	1.7 (0.8-2.5)	2.8 (2.6-3.0)	2.8 (2.4-3.2)	2.4 (1.7-3.1)
No. school days missed, mean, years	2.4 (2.2-2.6)	11.3 (10.7-11.9)	30.8 (23.1-38.5)	2.1 (1.9-2.3)	11.7 (11.1-12.2)	29.2 (23.9-34.5)
TPA, min/d	471.6 (464-478)	465.1 (446-483)	425.8 (377-474)	370.5 (360-380)	361.2 (342-380)	386.4 (349-422)
MVPA, min/d	88.8 (85-92)	83.9 (69-98)	63.5 (47-80)	28.8 (26-31)	25.8 (21-30)	27.2 (17-37)

Abbreviations: BMI, body mass index; MVPA, moderate to vigorous physical activity; NHANES, National Health and Nutrition Examination Survey; TPA, total physical activity (light + MVPA).

^aPoverty level assessed from the income-to-poverty ratio (range, 0-5).

^bAbsenteeism: minimal, 0 to 8 years; moderate, 9 to 17 years; severe, 18+ years.

^cValues in parentheses represent 95% confidence intervals.

Table 2 displays the weighted physical activity levels and number of school days missed across physical activity quartiles. Across all comparisons, those in the lowest quartile for MVPA and total physical activity had the most number of missed school days.

Table 2.

Weighted Physical Activity Levels and Number of School Days Missed Across Physical Activity Quartiles, 2003 to 2006 NHANES.^a

Variable	Children (n = 1249)				Adolescents (n = 1747)
	Total Physical Activity Quartile				Total Physical Activity Quartile
	1	2	3	4	1	2	3	4
TPA, mean, min/d	375.0 (368-381)	452.1 (450-454)	501.7 (499-504)	570.7 (562-578)	267.3 (260-274)	347.9 (345-350)	407.0 (404-409)	493.2 (485-500)
No. school days missed, mean, years	4.31 (3.3-5.3)	3.56 (2.7-4.3)	3.71 (3.0-4.4)	3.38 (2.8-3.9)	3.85 (2.9-4.7)	3.87 (3.1-4.6)	3.36 (2.5-4.1)	3.85 (3.0-4.6)
	MVPA Quartile				MVPA Quartile
	1	2	3	4	1	2	3	4
MVPA, mean, min/d	38.0 36-39)	70.2 (69-71)	100.4 (99-101)	151.0 (146-155)	6.1 (5.6-6.4)	18.2 (17.6-18.7)	32.3 (31.7-32.9)	65.1 (62.4-67.7)
No. school days missed, mean, years	4.23 (3.1-5.2)	3.84 (2.8-4.8)	3.56 (2.8-4.3)	3.36 (2.8-3.9)	4.28 (3.5-4.9)	3.57 (2.8-4.2)	3.31 (2.7-3.8)	3.70 (2.6-4.8)

Abbreviations: MVPA, moderate to vigorous physical activity; NHANES, National Health and Nutrition Examination Survey; TPA, total physical activity (light + MVPA).

^aValues in parentheses are 95% confidence intervals.

Table 3 displays the weighted multinomial logistic regression results, with results adjusted for age, gender, race–ethnicity, body mass index, and poverty level. For children, those in quartile 4 (vs 1) for total physical activity had an 89% reduced odds of having severe (vs no/minimal) absenteeism (odds ratio [OR] = 0.11; 95% confidence interval [CI]: 0.02-0.48); results were similar for MVPA. For adolescents, those in quartile 4 (vs 1) for MVPA had a 41% reduced odds of having moderate (vs no/minimal) absenteeism (OR = 0.59; 95% CI: 0.35-0.99). Given the U-shaped relationship observed by Hansen et al,⁷ additional analyses were computed that changed the referent group to those in physical activity quartiles 2 and 3. Quartile 4, for MVPA and total physical activity, did not have a significantly increased odds of severe absenteeism, when compared to quartiles 2 or 3 for either children or adolescents (data not shown). Additionally, unadjusted analyses were computed as well as adjusted analyses that excluded body mass index as a covariate; in both situations, results were similar to the fully adjusted results reported herein (data not shown).

Table 3.

Multinomial Logistic Regression Results (Rate Ratio, 95% CI) Examining the Association Between Physical Activity and Absenteeism Level Among Children and Adolescents, 2003 to 2006 NHANES.^a,b,c

Variable	Children (n = 1249)		Adolescents (n = 1747)
	Absenteeism Level		Absenteeism Level
	Moderate vs Minimal	Severe vs Minimal	Moderate vs Minimal	Severe vs Minimal
Total PA
Q2 vs Q1	0.74 (0.37-1.48)	0.69 (0.17-2.79)	0.87 (0.46-1.64)	1.50 (0.55-4.03)
Q3 vs Q1	0.99 (0.51-1.95)	0.19 (0.03-1.04)	0.82 (0.39-1.71)	0.91 (0.18-4.45)
Q4 vs Q1	0.76 (0.37-1.56)	0.11 (0.02-0.48)	0.64 (0.29-1.39)	1.82 (0.39-8.29)
MVPA
Q2 vs Q1	0.76 (0.41-1.40)	0.32 (0.04-2.36)	1.03 (0.56-1.92)	0.77 (0.23-2.48)
Q3 vs Q1	0.62 (0.21-1.81)	0.06 (0.01-0.56)	1.04 (0.54-1.99)	0.38 (0.06-2.34)
Q4 vs Q1	0.58 (0.23-1.49)	0.03 (0.3-0.25)	0.59 (0.35-0.99)	1.66 (0.42-6.44)

Abbreviations: CI, confidence interval; MVPA, moderate to vigorous physical activity; NHANES, National Health and Nutrition Examination Survey; PA, physical activity; TPA, total physical activity; Q, quartile.

^aMultinomial logistic regression models were computed separately for children and adolescents and for MVPA and TPA; 4 models in total were computed. In each model, covariates included age (continuous; years), gender, race–ethnicity (Mexican American, non-Hispanic white, non-Hispanic black, and other), body mass index (continuous; kg/m²), and poverty level (range, 0-5).

^bAbsenteeism: minimal, 0 to 8 years; moderate, 9 to 17 years; severe, 18+ years.

^cBold indicates statistical significance (P < .05).

When MVPA was treated as a continuous variable in a fully adjusted multinomial logistic regression model, MVPA was not associated with moderate absenteeism (vs no/minimal; OR = 1.00; 95% CI: 0.99-1.01), but a 1 min/d increase in MVPA was associated with a 3% reduced odds of severe absenteeism (vs no/minimal; OR = 0.97; 95% CI: 0.94-0.99) for children. The MVPA as a continuous variable was not associated with moderate absenteeism (OR = 0.99; 95% CI: 0.98-1.01) or severe absenteeism (OR = 1.00; 95% CI: 0.98-1.02) for adolescents. Results were similar when examining total physical activity as a continuous variable. For children, for a 1 min/d increase in total physical activity, they had a 1% reduced odds of severe absenteeism (OR = 0.991; 95% CI: 0.982-0.999), not significant for moderate absenteeism (OR = 1.00; 95% CI: 0.99-1.01). Similarly, for adolescents, total physical activity was not associated with moderate absenteeism (OR = 0.999; 95% CI: 0.996-1.002) or severe absenteeism (OR = 1.003; 95% CI: 0.996-1.01) when compared to those with no/minimal absenteeism.

Finally, multiplicative interaction analyses demonstrated no multiplicative interaction effects for MVPA and any of the covariates among the adolescent sample (all interaction terms, P > .05). For children, the only covariate that demonstrated a multiplicative interaction effect with MVPA was poverty level (interaction term for MVPA and poverty for moderate vs no absenteeism, OR = 0.99, P = .92; interaction term for MVPA and poverty for severe vs no absenteeism, OR = 0.98, P = .02). To illustrate this interaction effect among children, we created a 4-level categorical variable based on the median levels of their income-to-poverty ratio (median = 1.7) and MVPA (median = 83.8 min/d). These 4 groups included the following: (1) lower SES and less active; (2) lower SES and more active; (3) higher SES and less active; and (4) higher SES and more active. The proportion of children with severe absenteeism across these 4 respective groups was 4.7%, 1.7%, 2.0%, and 0%.

Discussion

Summary

The purpose of this study was to complement the recent findings by Hansen et al⁷ by employing an objective measure of physical activity. Although an U-shaped relationship was not observed with this objectively measured physical activity data, these findings support the notion that less physical activity (total and MVPA) is associated with severe absenteeism, particularly among children. That is, children with a greater degree of absenteeism engaged in less physical activity. We also observed an interaction effect of MVPA and poverty level on school absenteeism in children, suggesting that the risk of absenteeism may vary based on the joint effect of MVPA and poverty level. We specifically observed a higher rate of severe absenteeism among children who were less active and had a lower SES. The interactive effects of physical activity, school absenteeism, and poverty are complex and warrant future research to help clarify the direction of these interrelationships. For example, poverty may cause children to be sick, which in turn may cause them to be less active and absent more from school. Alternatively, poverty might cause inactive children to be sick and absent more often but not cause active children to be absent, because their physical activity may play a protective role in preventing certain illnesses.

Our somewhat discrepant findings when compared to those of Hansen et al may be a result of the different methods used to assess physical activity (subjective vs objective). Future prospective work employing both methodologies may help to further clarify this discrepancy, and future carefully designed studies should aim to better identify the directionality of the interrelationships between physical activity, school absenteeism, and poverty.

Limitations

Limitations of this study include the proxy (child) and self-report (adolescent) assessment of school absenteeism. Further, the cross-sectional study design does not allow for the temporal direction of this association to be determined. Among 1240 children, only 15 reported severe absenteeism. This may negatively affect the internal validity of the study. Further, the data presented herein are over 10 years old, and there is some suggestive evidence that children’s physical activity and sedentary behaviors have slightly changed over the last decade.^19,20 Thus, future prospective work utilizing more recent data on this topic is warranted, and in particular, such work should utilize absenteeism data confirmed from school records. Additionally, the manuscript may be subject to residual confounding, as, for example, NHANES depression data are not publically accessible for this population. Perhaps the biggest limitation of this study is that we are unable to identify potential mechanisms to explain our observed associations, which may help to identify the direction of our observed associations. That is, we are uncertain as to which parameters may be responsible for the association between physical activity and absenteeism and whether physical activity is causally related to absenteeism or whether absenteeism plays a greater role in influencing physical activity. Future work may wish to evaluate whether physical and mental health act as potential mediators or confounders in our evaluated relationship.

Significance

The NHANES measure of school absenteeism evaluated the number of missed school days due to illness or injury. The specific reasons for missed schools were not evaluated, so understanding specific potential mechanisms to explain the observed associations is difficult. However, research demonstrates that, among youth, physical activity is associated with better overall perceived health.²¹ Although speculative, this may be 1 potential mechanism to explain the observed associations, in that physically active children may have fewer missed school days due to poor health/injury because of the better overall health associated with physical activity. We were not able to fully evaluate this potential underlying mechanism, as in the present study, perceived overall health status was only assessed among the adolescent NHANES sample. In the adolescent sample, the only significant association was that adolescents in quartile 4 (vs 1) for MVPA had a 41% reduced odds of having moderate (vs no/minimal) absenteeism (OR = 0.59; 95% CI: 0.35-0.99). When adding perceived health status (excellent, very good, good, fair, or poor) as a covariate in this model, this association was slightly attenuated and no longer statistically significant (OR = 0.62; 95% CI: 0.36-1.07), providing some support for the assertion that general health status may mediate the relationship between physical activity and school absenteeism due to illness or injury.

These findings of an association between higher MVPA and less school absenteeism may provide useful information for health professionals. Further, not only may physical activity help to foster school attendance but also empirical evidence suggests that physically active school-aged children, compared to their less active counterparts, perform better academically.⁶ Thus, physical activity promotion among this population is of critical importance. The following narrative provides potential physical activity promotion strategies among this population, which may help to foster regular school attendance. Of course, these recommendations would only be valid in promoting school attendance if, indeed, there is a causal relationship between physical activity and school absenteeism. A potential strategy to accomplish this is to foster a collaborative relationship between school officials and the children’s parents. Consistent work, for example, demonstrates that parental support for child physical activity plays a key role in facilitating child physical activity behavior.^22

-25 As an example, this could be accomplished by integrating family-based physical activities as part of the child’s homework. Another strategy to help accomplish this necessity of increasing children’s physical activity is to continue to lobby for year-round, daily physical education.²⁶ Three widely disseminated, evidenced-based school physical education curriculums that schools can adopt are the Sports Play and Active Recreation for Kids curriculum,²⁷ the Child and Adolescent Trial for Cardiovascular Health program,²⁸ and the Lifestyle Education for Activity Program.²⁹ In addition to physical education at school, after-school programs have the capacity to reach large numbers of children and are thought to provide opportunities for children to engage in regular physical activity.³⁰ Finally, emerging work demonstrates that integrating physical activity during the instructional curriculum can help to facilitate child physical activity and improve educational learning.³¹ Taken together, these findings suggest that school officials, in particular, may help to facilitate child school attendance and child physical activity through family-based homework activities, dissemination of appropriate physical education curriculum, physical activity-based after-school programs, and when appropriate, integration of physical activity in the instructional curriculum.

SO WHAT?

What is already known on this topic?

Self-reported physical activity is associated with school absenteeism. An U-shaped relationship exists between self-reported physical activity and school absenteeism, wherein absenteeism is increased among children reporting both low and high levels of physical activity. Moderate levels of physical activity appear to have no relationship to occurrences of absenteeism.

What does this article add?

Objectively measured physical activity is associated with school absenteeism.

What are the implications for health promotion practice or research?

Given the observed interaction effect of MVPA and poverty level on school absenteeism, coupled with the knowledge of lower MVPA and more missed school days among those with a lower income-to-poverty ratio, particular attention for promoting physical activity and closely monitoring school absenteeism among youth of a low income-to-poverty ratio may be warranted.

In conclusion, higher levels of accelerometer-assessed physical activity were associated with lower odds of severe school absenteeism, particularly among children. Such an observation is important, particularly if confirmed by more robust study designs, as school absenteeism strongly contributes to academic performance.

Footnotes

Acknowledgments

The authors would like to thank the NHANES personnel for all their work on the NHANES project, as this study would not have been possible without them. The authors also acknowledge and thank the NHANES participants.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

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