Screen Time Viewing Behaviors and Isometric Trunk Muscle Strength in Youth : Medicine & Science in Sports & Exercise

Journal Logo

EPIDEMIOLOGY

Screen Time Viewing Behaviors and Isometric Trunk Muscle Strength in Youth

GRØNTVED, ANDERS1; RIED-LARSEN, MATHIAS1; FROBERG, KARSTEN1; WEDDERKOPP, NIELS1; BRAGE, SØREN1,2; KRISTENSEN, PETER LUND1; ANDERSEN, LARS BO1,3; MØLLER, NIELS CHRISTIAN1

Author Information
Medicine & Science in Sports & Exercise 45(10):p 1975-1980, October 2013. | DOI: 10.1249/MSS.0b013e318295af56
  • Free

Abstract

TV viewing and computer use—two very common sedentary behaviors among youth—are usually performed in a seated or lying posture for longer periods. The number of daily switches between seated/lying and standing/walking positions is likely to be affected by excessive time spent on these viewing behaviors. Thus, besides displacing time spent on physical activity, excessive screen time use may also influence posture allocation, which could explain part of the adverse health effects of screen time viewing reported on outcomes such as type 2 diabetes, cardiovascular diseases, premature mortality, and its biological risk factors (5,8,10,26). Several previous studies have shown that prolonged screen time viewing in childhood or youth may lead to poorer cardiorespiratory fitness (CRF) later in life independent of the level of physical activity and other determinants of CRF (12,20). However, time spent in the seated or lying posture, a reduced number of posture transitions, and less time spent on physical activity as a result of excessive viewing time could also influence muscle strength, in particular, trunk muscle strength. To further explore whether screen time viewing behaviors influence trunk muscle strength, we examined the association of screen time behaviors with abdominal and back isometric strength in a population sample of Danish youth with adjustment for potential confounding factors such as CRF.

METHODS

Design

This study was cross-sectional and used data from the Danish European Youth Heart Study, an international population-based multicenter study that addresses cardiovascular disease risk factors in children and adolescents (23). For this particular investigation, the eligible participants were 429 adolescents from the assessment wave in 1997–1998 and 444 adolescents from the 2003–2004 wave. In 1997–1998, a subgroup of 243 participants had isometric muscle strength assessed, and in 2003–2004, n = 441 had isometric muscle strength evaluated. The local scientific ethics committee approved the study, and all participants gave informed consent to participate.

TV, computer use, and total screen time viewing

TV viewing and computer use during leisure was obtained by self-report using a computer-based questionnaire (10). Two questions were asked about the amount of TV viewing time (before and after school). From these two questions, a summary of daily TV viewing time variable was constructed (h·d−1). Daily time spent using computer was asked in one question. A total screen time variable (h·d−1) was created by summarizing TV and computer use.

Muscle strength

Isometric muscle strength was obtained during maximal voluntary contraction (MVC) of abdominal and back muscles using a strain gauge dynamometer (1). The participants were standing upright and positioned with a strap around the shoulders connected to the dynamometer. Abdominal MVC was performed with the back against the dynamometer performing maximal forward flexion. For MVC of the lower back muscles, the participants were positioned with the front against the dynamometer, performing maximal backward extension. We expressed total isometric trunk muscle strength (N) as the mean of abdominal and back strength relative to body weight (N·kg−1). Previous studies have reported a high reliability of these particular isometric strength measures in adults (intraclass correlation coefficient >0.9) (6).

CRF

We assessed CRF during a progressive maximal ergometer bicycle test (Ergomedic 839; Monark, Varberg, Sweden) (23). HR was recorded every 5 s during the test using an HR monitor (Polar Vantage, Polar Electro Oy, Kempele, Finland). Criteria for a maximal effort were HR ≥185 bpm and a subjective judgment by the observer that the participant could no longer continue, even after verbal encouragement. Maximal power output (wattmax) was used to estimate maximal oxygen uptake using the following equation: V˙O2max (mL O2·min−1·kg−1) = 0.465 + (0.0112 × wattmax) + (0.172 × gender)/body weight (kg), where gender is as follows: boys = 1 or girls = 0 (15). The fitness measure is highly reproducible (coefficient of variation, 2.5%–4.8%), and a previous validation study among 15-yr olds have shown that this measure is highly correlated with directly measured V˙O2max (r > 0.90, P < 0.001) (2).

Other covariates

Height and weight were measured while the participants were wearing light clothing, without shoes, using standard anthropometric procedures. Waist circumference (WC) was measured to the nearest 1 mm at the midpoint between the lower ribs and the iliac crest with a flexible tape. Smoking status (yes/no) and monthly frequency soft drinks, fruit, and vegetable intake were obtained by self-report in adolescence using a computer-based questionnaire as described previously (23). Parental educational level was obtained by parental self-report. Parental educational status was defined according to the International Standard Classification of Education (ISCED) (UNESCO 1997). However, because the details obtained of the description of education were insufficient, the ISCED seven-point scale was combined into three new groups (I = level 1–2, II = level 3–4, and III = level 5–7). Moderate and vigorous physical activity (MVPA) was assessed using accelerometry with data reduction as described previously (18). Specifically, an accelerometer output >2000 counts·min−1 (equivalent to walking about 4 km·h−1) was defined as MVPA and expressed as percentage of total registered time.

Statistics

Associations of TV viewing, computer use, and total screen time use with isometric trunk muscle strength (standardized score (SD)) was analyzed using multivariable adjusted linear regression. Initially, we ran models adjusting for age, sex, recruitment wave, parental educational status, smoking status, intake of soft drinks, and fruit and vegetable intake. We then ran analyses with additional adjustment for CRF and WC. We also ran a multivariable adjusted model including both TV viewing and computer use in the same model to assess whether both types of screen-based behavior were associated with isometric trunk muscle strength, independent of each other.

We also examined the association of screen time use with isometric trunk muscle strength by CRF level, parental educational level, and sex. Interaction between screen time and these factors was examined by including interaction terms with main effects included in the multivariable models.

In sensitivity analyses, we additionally adjusted for accelerometry-measured MVPA to examine if any residual confounding by physical activity remained that CRF may not have captured. Because 37% of the participants with otherwise full data had missing information on accelerometer-measured MVPA, we imputed missing values on MVPA using a multiple linear regression imputation approach (“mi impute” in STATA), including all covariates and the outcome. We obtained beta coefficients and SE on the basis of 20 imputed data sets while the variability between imputations is adjusted for (24).

All statistical analyses were performed in STATA 12.1 with alpha = 0.05 (two sided).

RESULTS

The present study included a total of 606 adolescents 14–16 yr old, of whom 205 were recruited in 1997/1998 and 401 in 2003/2004. Table 1 shows selected characteristics of the included participants in the present study compared with participants excluded because of missing data (n = 267). There were no differences between included participants and individuals with missing data in majority of the characteristics, except for age, gender, and TV viewing time. Individuals with missing data were slightly older and viewed more TV, and the percentage of boys compared with girls was lower (Table 1). The mean screen time was 2.8 h·d−1 among boys and 1.8 h·d−1 among girls participating in the study. The Spearman correlation coefficient between TV viewing and computer use was 0.10 (P = 0.02).

T1-17
TABLE 1:
Characteristics of the study population by gender and attrition analyses.

The associations of TV viewing, computer use, and total screen time with isometric trunk muscle strength in youth are shown in Table 2. In basic multivariable adjusted models without adjustment for CRF and WC, all screen time behaviors were significantly associated with abdominal, back, and total isometric trunk muscle strength. After further adjustment for fitness and WC, associations of computer use and total screen time use were moderately attenuated but were still associated with both abdominal, back, and total isometric trunk muscle strength (P < 0.05). Each 1 h·d−1 difference in total screen time was associated with −0.09 (95% confidence interval (CI), −0.14 to −0.04) SD difference in isometric trunk muscle strength in fully adjusted analysis. TV viewing was marginally associated with total isometric trunk muscle strength in fully adjusted models (−0.05 (95% CI, −0.11 to 0.005) SD difference in strength per 1 h·d−1 difference in viewing time, P = 0.08). There were no indications that screen time was nonlinearly associated with isometric trunk muscle strength, on the basis of either visual inspection (Fig. 1) or statistical evaluation by including a quadratic term of total screen time in the fully adjusted multivariable model (P = 0.12). Results were unaltered when adjusting the analyses for waist-to-height ratio or body mass index instead of WC (data not shown). Additional adjustment for accelerometer-measured MVPA did not alter the associations; each 1 h·d−1 difference in total screen time was associated with −0.08 (95% CI, −0.13 to −0.03) SD difference in isometric trunk muscle strength in fully adjusted analysis including WC and CRF. When we included TV viewing and computer use in the model, the estimates of association with isometric trunk muscle strength was close to similar compared with the analyses of each viewing type analyzed separately (betacomputer = −0.18 (95% CI, −0.27 to −0.08) SD, betaTV = −0.05 (95% CI, −0.11 to 0.008) SD, P = 0.09). We also examined if isometric trunk muscle strength was different according to achievement of youth recommendations for screen time (≤2 h·d−1). Adolescents not exceeding the recommended levels for screen time (4,27) had −0.18 (95% CI, −0.32 to −0.04) SD difference in isometric trunk muscle strength, compared with adolescents achieving recommendations (P = 0.01).

T2-17
TABLE 2:
Association of TV viewing, computer use, and total screen time viewing (h·d−1) with isometric trunk muscle strength (SD) in youth.
F1-17
FIGURE 1:
Total isometric muscle strength (back and front trunk) against total screen time (TV viewing and computer use) in a population sample of Danish youth. Estimates with 95% CI are from fully adjusted multiple regression analysis (model 3, Table 2).

We also analyzed the association of screen time with CRF adjusting for the same covariates including total isometric trunk muscle strength and WC. Each 1 h·d−1 difference in total screen time was associated with −0.04 (95% CI, −0.08 to −0.01) SD difference in CRF in this analysis (P = 0.02).

We then ran analyses of the association of total screen time with total isometric trunk muscle strength stratified by sex-specific quartiles of CRF, parental educational level, and sex (Fig. 2). In these analyses, we did not see statistical evidence of interaction between these factors and screen time (P > 0.3 for all interactions).

F2-17
FIGURE 2:
Association of total screen time viewing (TV viewing and computer use (h·d−1)) with isometric trunk muscle strength (SD) in youth stratified by fitness (sex-specific quartiles), parental educational level (basic or secondary education/tertiary education), and sex. Estimates with 95% CI are from fully adjusted multiple regression analysis (model 3, Table 2). P = 0.91 for fitness-by-screen time interaction, P = 0.97 for educational level-by-screen time interaction, and P = 0.36 for sex-by-screen time interaction on trunk muscle strength.

DISCUSSION

In this cross-sectional study of a population sample of Danish youth, excessive screen time behaviors were associated with lower isometric trunk muscle strength. Importantly, these inverse associations were independent of CRF, general or abdominal adiposity, and other lifestyle and sociodemographic factors. Furthermore, we did not see any indication that the association of screen time use with muscle strength was attenuated among high-fit individuals, which suggests that limiting screen time use could be beneficial for improving or maintaining isometric trunk muscle strength even among cardiorespiratory fit individuals. Because daily excessive time spent in a seated or lying position is likely to reduce exposure to postures requiring greater muscle tone and potentially also posture transitions, this could explain these inverse associations. We adjusted our analyses for CRF to capture current and long-term engagement in physical activity, which undoubtedly is an important confounder in the relation of screen time exposure with muscle strength. We cannot rule out that residual confounding remained for CRF and physical activity. Furthermore, because excessive computer use and TV viewing are associated with other unhealthy behaviors including concomitant intake of unhealthy foods, and TV advertisements and TV/computer content may influence other unhealthy behaviors, it could be that the inverse associations of these viewing behaviors with isometric trunk muscle strength are explained by factors, which we have not fully adjusted for.

We are aware of only one other study examining the association of screen time and isometric trunk muscle strength. Our study is in agreement with a cross-sectional study among Finnish young adults that reported an inverse association of TV viewing with isometric trunk muscle strength assessed using similar procedures (21). These associations were reported being independent of self-reported “brisk” physical activity and smoking status but were not adjusted for CRF and other lifestyle and sociodemographic factors. Furthermore, the evaluation neither included computer use nor made sequential adjustment for adiposity, so it is not unlikely that reported associations have a larger degree of confounding by adiposity and other unmeasured factors associated with young adult lifestyle. The observations from our study are also supported by findings from a prospective study of Canadian toddlers followed until the second grade (7). In that study, increases in parentally reported TV viewing time between the age of 2.5 and 4.5 yr predicted shorter long-jump performance at 8 yr old independent of parentally reported physical activity and other characteristics including child weight status at follow-up. Finally, two cross-sectional studies carried out in the 1970s and early 1980s have reported inverse associations of TV viewing time with components of muscle strength and fitness (14,28).

We are not aware of randomized trials examining the effect of reducing any type of sedentary behavior, including screen-based behaviors on muscle strength. However, a small-scale randomized trial has examined the effect of changing school furniture to adjustable desks and chairs with sitting trunk–thigh angle adjusted to 135° compared with traditional school desks and chairs with sitting trunk–thigh angle of 90° for a period of 2 yr among high school student. This study found that the intervention increased abdominal and back muscle strength (16). These results support the notion that specific postures while sitting are important for developing or maintaining trunk muscle strength. We have previously reported that low isometric MVC of the trunk and prolonged screen time use in youth are associated with greater adiposity, insulin resistance, and raised levels of other cardiovascular risk factors in young adulthood independent of CRF (9,11). Thus, limiting screen time use or introducing more standing while engaging in screen time could be important targets for maintaining isometric trunk muscle strength and subsequently in preventive measures against development of insulin resistance and other metabolic abnormalities later in life. Clearly, more evidence from experimental studies is needed on this topic to infer, with greater confidence, that these associations are causal and to test the effectiveness of interventions such as standing desks on physical fitness and other health outcomes.

The major strength of the study was that we were able to adjust our analyses for a range of important confounding factors including CRF. Furthermore, we assessed isometric trunk muscle strength using a highly reliable method. We were also able to examine both TV viewing time and computer use separately, which are two analog behaviors in the sense that both behaviors are usually performed seated or in a lying position and likely to reduce exposure to posture requiring greater muscle tone. Because associations with isometric trunk muscle strength for both types of viewing behavior were unaffected by mutual adjustment, this strengthens the inference that posture allocation or sitting/lying time explains the associations. Besides the possibility that residual and unknown confounding could explain the results, there are some additional limitations to the study. The inverse associations of screen time use and muscle strength could also be a result of reverse causality; i.e., screen time use increases as a result of poor strength. Because our study was cross-sectional, we could not tease out the extent of this possible reverse causation bias. Although we did not see a sex-by-screen time use interaction on muscle strength, sex-stratified analyses indicated that associations were less strong for girls and larger studies are needed to further examine this. Furthermore, the assessments of screen time viewing behaviors were based on self-report, and we cannot rule out the possibility of recall bias (i.e., that screen time use is over- or underestimated dependent on the level of isometric trunk muscle strength). Reliability of self-reported screen use among adolescents has been reported moderate to excellent (3,13,22,25,29), and validity against diary as the criterion measure has been reported moderate (25,29). We did not analyze associations of accelerometer-measured sedentary time or breaks in sedentary time with isometric trunk muscle strength. Although accelerometers worn on the hip are commonly used to objectively assess physical activity on the basis of a large pool of extensive validation studies, a hip-mounted accelerometer is less suitable to assess activity in the lower spectrum of the activity continuum (sedentary behavior) and can only poorly distinguish between sitting and standing or characterize breaks in sitting time (17,19). Furthermore, the use of accelerometry in the assessment of sedentary time and components of sedentary time such as breaks have not been rigorously evaluated with respect to the effect of data reduction choices and participant adherence to monitoring protocol on error in estimation of sedentary time in association analyses with health outcomes. In addition, although the isometric muscle strength assessment procedures are very reliable in adults, we did not evaluate reliability of the tests in youth, which remains to be determined.

In summary, in a population sample of Danish youth, screen time use was inversely associated with isometric trunk muscle strength independent of CRF, lifestyle behaviors, adiposity, and sociodemographic factors. Further studies are needed to disentangle whether the prolonged time spent in a seated or lying position and possibly fewer posture allocations are driving this association, which would therefore be important behavioral intervention targets for maintaining trunk muscle strength.

This work was supported by the Danish Heart Foundation, the Danish Health Fund (Sygekassernes Helsefond).

The authors declare no conflicts of interest.

The results of the present study do not constitute endorsement by the American College of Sports Medicine.

REFERENCES

1. Andersen LB, Henckel P. Maximal voluntary isometric strength in Danish adolescents 16–19 years of age. Eur J Appl Physiol Occup Physiol. 1987; 56 (1): 83–9.
2. Anderssen SA, Cooper AR, Riddoch C, et al. Low cardiorespiratory fitness is a strong predictor for clustering of cardiovascular disease risk factors in children independent of country, age and sex. Eur J Cardiovasc Prev Rehabil. 2007; 14 (4): 526–31.
3. Atkin AJ, Gorely T, Clemes SA, et al. Methods of measurement in epidemiology: sedentary behaviour. Int J Epidemiol. 2012; 41 (5): 1460–71.
4. Committee on Public Education. Children, adolescents, and television. Pediatrics. 2001; 107 (2): 423–6.
5. Dunstan DW, Kingwell BA, Larsen R, et al. Breaking up prolonged sitting reduces postprandial glucose and insulin responses. Diabetes Care. 2012; 35 (5): 976–83.
6. Essendrop M, Schibye B, Hansen K. Reliability of isometric muscle strength tests for the trunk, hands and shoulders. Int J Ind Ergon. 2001; 28 (6): 379–87.
7. Fitzpatrick C, Pagani LS, Barnett TA. Early childhood television viewing predicts explosive leg strength and waist circumference by middle childhood. Int J Behav Nutr Phys Act. 2012; 9 (1): 87.
8. Grøntved A, Hu FB. Television viewing and risk of type 2 diabetes, cardiovascular disease, and all-cause mortality: a meta-analysis. JAMA. 2011; 305 (23): 2448–55.
9. Grøntved A, Ried-Larsen M, Ekelund U, Froberg K, Brage S, Andersen LB. Independent and combined association of muscle strength and cardiorespiratory fitness in youth with insulin resistance and beta-cell function in young adulthood: The European Youth Heart Study. Diabetes Care. In press.
10. Grøntved A, Ried-Larsen M, Møller NC, et al. Youth screen time behaviour is associated with cardiovascular risk in young adulthood: The European Youth Heart Study. Eur J Prev Cardiol. In press.
11. Grøntved A, Ried-Larsen M, Møller NC, et al. Muscle strength in youth and cardiovascular risk in young adulthood: The European Youth Heart Study. Br J Sports Med. In press.
12. Hancox RJ, Milne BJ, Poulton R. Association between child and adolescent television viewing and adult health: a longitudinal birth cohort study. Lancet. 2004; 364 (9430): 257–62.
13. Hardy LL, Booth ML, Okely AD. The reliability of the Adolescent Sedentary Activity Questionnaire (ASAQ). Prev Med. 2007; 45 (1): 71–4.
14. Katzmarzyk PT, Malina RM, Song TMK, Bouchard C. Television viewing, physical activity, and health-related fitness of youth in the Québec family study. J Adolesc Health. 1998; 23 (5): 318–25.
15. Kolle E, Steene-Johannessen J, Andersen LB, Anderssen SA. Objectively assessed physical activity and aerobic fitness in a population-based sample of Norwegian 9- and 15-year-olds. Scand J Med Sci Sports. 2010; 20 (1): e41–7.
16. Koskelo R, Vuorikari K, Hänninen O. Sitting and standing postures are corrected by adjustable furniture with lowered muscle tension in high-school students. Ergonomics. 2007; 50 (10): 1643–56.
17. Kozey-Keadle S, Libertine A, Lyden K, Staudenmayer J, Freedson PS. Validation of wearable monitors for assessing sedentary behavior. Med Sci Sports Exerc. 2011; 43 (8): 1561–156.
18. Kristensen P, Moeller N, Korsholm L, et al. The association between aerobic fitness and physical activity in children and adolescents: the European youth heart study. Eur J Appl Physiol. 2010; 110 (2): 267–75.
19. Lyden K, Kozey Keadle SL, Staudenmayer JW, Freedson PS. Validity of two wearable monitors to estimate breaks from sedentary time. Med Sci Sports Exerc. 2012; 44 (11): 2243–52.
20. Mitchell JA, Pate RR, Blair SN. Screen-based sedentary behavior and cardiorespiratory fitness from age 11 to 13. Med Sci Sports Exerc. 2012; 44 (7): 1302–9.
21. Paalanne NP, Korpelainen RI, Taimela SP, et al. Muscular fitness in relation to physical activity and television viewing among young adults. Med Sci Sports Exerc. 2009; 41 (11): 1997–2002.
22. Rey-López JP, Ruiz JR, Ortega FB, et al. Reliability and validity of a screen time-based sedentary behaviour questionnaire for adolescents: The HELENA study. Eur J Public Health. 2012; 22 (3): 373–7.
23. Riddoch C, Edwards D, Page A, et al. The European Youth Heart Study—cardiovascular disease risk factors in children: rationale, aims, design and validation of methods. J Phy Act Health. 2005; 2: 115–29.
24. Rubin DB. Multiple imputation after 18+ years. J Am Stat Assoc. 1996; 91 (434): 473–89.
25. Schmitz KH, Harnack L, Jacobs DR Jr, et al. Reliability and validity of a brief questionnaire to assess television viewing and computer use. J Sch Health. 2004; 74 (9): 370–7.
26. Stamatakis E, Hamer M, Dunstan DW. Screen-based entertainment time, all-cause mortality, and cardiovascular events: population-based study with ongoing mortality and hospital events follow-up. J Am Coll Cardiol. 2011; 57 (3): 292–9.
27. Tremblay MS, LeBlanc AG, Janssen I, et al. Canadian sedentary behaviour guidelines for children and youth. Appl Physiol Nutr Metab. 2011; 36 (1): 59–64.
28. Tucker LA. The relationship of television viewing to physical fitness and obesity. Adolescence. 1986; 21 (84): 797–806.
29. Vereecken CA, Todd J, Roberts C, Mulvihill C, Maes L. Television viewing behaviour and associations with food habits in different countries. Public Health Nutr. 2006; 9 (02): 244–50.
Keywords:

FITNESS; TV; COMPUTER; ADOLESCENTS; SEDENTARY

© 2013 American College of Sports Medicine