GRAPHICAL ABSTRACT

INTRODUCTION

Sedentary behavior is defined as any waking activity with an energy expenditure of 1.5 metabolic equivalents (METs) or less [1]. It is a known risk factor for cardiovascular diseases and metabolic syndrome, contributing to increased body fat and diminished physical fitness [2,3]. Furthermore, the duration of sedentary behavior is strongly associated with muscle weakness, involving the loss of both muscle mass and strength [4-7]. Particularly in children and adolescents, robust evidence links sedentary behavior, specifically that involving screen time, to obesity [8]. However, because sedentary behaviors represent modifiable risk factors, addressing them among adolescents is crucial. Reducing these behaviors can help decrease the likelihood of adverse health outcomes in both youth and adulthood, thus conferring long-term health benefits [2,3,9,10].

Sedentary behaviors are highly prevalent among the youth population, with recent increases observed in overall sedentary lifestyles and screen-based sedentary behaviors, such as watching TV, playing video games, and using computers, tablets, and mobile phones [11]. More than 80% of adolescents across 105 countries are physically inactive, engaging in less than 60 minutes of moderate-to-vigorous physical activity (MVPA) daily [12]. In Canada, only 17.5% of children and adolescents meet the recommended duration of activity outlined in the 24-Hour Movement Guidelines, including 29.6% of children aged 5 years to 13 years and only 5.5% of adolescents aged 14 years to 17 years [13].

Health-related physical fitness encompasses cardiovascular endurance, muscular strength, muscular endurance, flexibility, and body composition. In youth, physical fitness reflects an individual’s capacity to engage in physical activities (PAs) resents an indicator of current and future health status [14]. Although sedentary behavior or sedentary time is associated with certain fitness indicators in adolescents, findings from previous studies have been inconsistent and subject to debate [3,10,15-21]. Notably, few studies have explored the link between sedentary lifestyle and skeletal muscle strength in this age group [10,15,16]. Consequently, the present research was conducted to investigate the relationship between sedentary lifestyle and both skeletal muscle strength and mass, as measured by handgrip strength (HGS) and appendicular lean mass (ALM), within the United States adolescent population. Furthermore, considering the 2020 World Health Organization (WHO) guidelines, which propose that substituting sedentary time with MVPA may confer health benefits [11], we also investigated the relationship between sedentary lifestyle, muscle strength, and mass by stratifying PA levels into none, moderate, and vigorous intensity.

METHODS

Study Population

The data utilized were combined from 2 cycles of the National Health and Nutrition Examination Survey (NHANES), specifically 2011-2012 and 2013-2014. The NHANES is a nationally representative survey of the non-institutionalized civilian population in the United States. It employs a complex, multistage probability sampling design to ensure a representative population.

This study initially included 1631 adolescents aged between 15 years and 19 years. Participants lacking physical fitness measures, such as HGS (n=105), ALM (n=206), and body mass index (BMI; n=70), or who did not respond to questions regarding sedentary lifestyle and PA (n=31), were excluded. Additionally, 158 participants with missing covariate variables, such as the poverty income ratio (PIR), were also excluded. Ultimately, the eligible adolescent population comprised 1449 individuals.

Sedentary Behavior Assessment

Data on daily sedentary behavior were collected using the NHANES self-reported lifestyle questionnaire, which is based on the Global Physical Activity Questionnaire framework. Participants were asked the question “How much time do you usually spend sitting on a typical day?” to quantify their daily sedentary behavior in hours. Time spent sleeping was explicitly excluded from this assessment.

Measurement of Skeletal Muscle Strength and Mass

HGS, body composition, and anthropometric parameters were assessed to evaluate skeletal muscle strength and mass.

HGS is widely recognized as a potent indicator of whole-body strength and has been shown to correlate with BMI, weight, and height [22-24]. For the assessment of muscle strength, the NHANES utilizes isometric HGS, measured in kilograms, using a digital handgrip dynamometer (model T.K.K.5401; Takei Scientific Instruments, Tokyo, Japan). While standing, participants were instructed to squeeze the dynamometer as hard as possible 3 times with each hand. Each value was recorded, and the highest HGS value among the 6 attempts was used for subsequent data analysis.

For the assessment of muscle mass, the NHANES utilized dual-energy X-ray absorptiometry (DXA) to quantify lean soft tissue and fat mass with a fan beam X-ray bone densitometer (Hologic Discovery A; Hologic Inc., Marlborough, MA, USA). Records of whole-body DXA scans were retrieved, and the aggregate value of ALM, representing the sum of both arms and legs excluding bone mineral content and expressed in kilograms, was employed in the analyses.

Both HGS and ALM were adjusted for BMI and weight to account for differences in body size, as described in previous studies [24,25].

Variables of Interest

Data regarding the following potential confounders were collected through questionnaires and examinations: age (treated as a continuous variable), sex (categorized as male or female), and ethnicity (classified as non-Hispanic white, non-Hispanic black, Mexican or other Hispanic, non-Hispanic Asian, or other). PIR was expressed as a ratio of family income to the poverty threshold (with a value of less than 1 thus indicating a family income below the poverty line) and was divided into 3 groups —low, <1.3; middle, 1.3 to <3.5; and high, ≥3.5—based on the Department of Health and Human Services poverty guidelines and prior research [26]. MVPA was included as a covariate because the second edition of the Physical Activity Guidelines for Americans (2018) and the WHO Guidelines on Physical Activity and Sedentary Behavior (2020) recommend vigorous-intensity PA for youths aged 6 years to 17 years and 5 years to 17 years, respectively [11,27].

Statistical Analysis

Analysis of variance (ANOVA) or the Student t-test was employed to assess statistical differences in the distribution of daily sedentary time and all outcome variables across covariates.

Correlations between daily sedentary time (both as a continuous variable and categorized into quartiles) and each outcome variable were examined. For trend analysis, daily sedentary time was divided into the following quartiles: less than 7 hr/day (Q1), 7 to less than 9 hr/day (Q2), 9 to less than 11 hr/day (Q3), and 11 or more hr/day (Q4). These quartile groups (Q1 to Q4) were treated as categorical variables, with Q1 serving as the reference group for trend testing. To evaluate the association between daily sedentary time and each outcome variable (HGS, HGS/BMI, HGS/weight, ALM, ALM/BMI, and ALM/weight), linear regression analyses were conducted using PROC SURVEYREG. Three regression models were constructed to account for potential confounders: a crude model, which did not adjust for any covariates; model 1, which adjusted for age, sex, ethnicity, and PIR; and model 2, which adjusted for all covariates from model 1 plus MVPA. In accordance with the NHANES analytic and reporting guidelines, all analyses utilized weighted estimates of the population parameters to reflect the complex sampling design. All statistical analyses were performed using SAS version 9.4 (SAS Institute Inc., Cary, NC, USA).

Ethics Statement

The NHANES constitutes a publicly available national statistical database without personally identifiable information. Therefore, this secondary analysis of the data did not require institutional review board approval.

RESULTS

Characteristics of the Study Population: Distribution of Daily Sedentary Time, Skeletal Muscle Strength, and Mass Parameters by Participant Characteristics

Table 1 presents the characteristics of the study population, presented as number of participants (n) with percentage (%) or—for daily sedentary time, skeletal muscle strength, and mass parameters—as mean±standard deviation. Additionally, p-values (based on ANOVA or t-tests) are displayed for each variable.

Daily sedentary time differed significantly according to age, sex, ethnicity, PIR, and MVPA. The mean daily sedentary time was greater in female participants (p<0.001), those who were younger (with the highest sedentary time at 15 years of age and decreasing thereafter; p<0.001), individuals identifying as Asian or another ethnicity (p=0.003), those with a higher family income (PIR ≥3.5; p<0.001), and those who did not engage in MVPA (p=0.008) (Table 1).

Absolute HGS varied significantly by sex, age, ethnicity, and MVPA. The mean HGS was higher in participants who were male (p<0.001), were older (increasing with age until displaying its highest value at age 19; p<0.001), were of black or other ethnicity (p<0.001), and engaged in MVPA (p<0.001). However, no significant difference in absolute HGS was observed among participants in terms of PIR. A distinct pattern was observed for relative HGS. HGS/BMI differed significantly by sex (p<0.001), ethnicity (p<0.001), PIR (p=0.037), and MVPA category (p<0.001). HGS/weight exhibited significant differences by sex (p<0.001) and MVPA category (p<0.001) (Table 1).

Absolute ALM differed significantly by sex, age, ethnicity, and MVPA. The mean absolute ALM was higher in participants who were male (p<0.001), older (displaying its highest value at age 19; p=0.012), and of black or other ethnicity (p<0.001), as well as those who engaged in MVPA (p<0.001). However, no significant difference in absolute ALM was observed among participants regarding PIR (p =0.809). A similar pattern was observed for relative ALM; both ALM/BMI and ALM/weight differed significantly by sex, ethnicity, and MVPA category (all p<0.001) but exhibited no significant differences with respect to age or PIR (Table 1).

All outcome variables differed significantly across daily sedentary time quartiles (p<0.001 for all comparisons; Table 1).

Table 2 presents the beta coefficients (β) and standard errors (SEs) for the associations between daily sedentary time and the examined skeletal muscle strength and mass parameters, namely HGS, HGS/BMI, HGS/weight, ALM, ALM/BMI, and ALM/weight. The crude model revealed significant associations between daily sedentary time and these parameters.

In model 1, all parameters except absolute ALM demonstrated significant associations with daily sedentary time. In model 2, HGS (β, -0.265; SE, 0.074; p=0.001), HGS/BMI (β, -0.021; SE, 0.004; p<0.001), HGS/weight (β, -0.008; SE, 0.002; p<0.001), ALM/BMI (β, -0.008; SE, 0.003; p=0.010), and ALM/weight (β, -0.003; SE, 0.001; p=0.005) were significantly associated with daily sedentary time. However, absolute ALM did not exhibit a significant relationship with daily sedentary time (Table 2).

Table 3 summarizes the β and SE values for the relationships between daily sedentary time and the examined skeletal muscle strength and mass parameters, stratified by the type of PA reported by the participants: none, moderate, or vigorous intensity.

In the group with no PA, HGS (β, -0.269; SE, 0.113; p=0.024), HGS/height (β, -0.127; SE, 0.055; p =0.026), HGS/weight (β, -0.007; SE, 0.003; p =0.009), and ALM/weight (β, -0.002, SE, 0.001; p=0.041) were significantly associated with daily sedentary time after adjusting for age, sex, ethnicity, and PIR. In contrast, ALM and ALM/BMI showed no significant relationships with daily sedentary time. In the moderate PA group, HGS (β, -0.344; SE, 0.135; p=0.016), HGS/height (β, -0.194; SE, 0.073; p=0.012), ALM/BMI (β, -0.013, SE, 0.005; p=0.016), and ALM/weight (β, -0.004; SE, 0.002; p=0.016) were significantly associated with daily sedentary time after adjusting for all covariates. However, absolute ALM was not significantly related to daily sedentary time. In the vigorous PA group, HGS/height (β, -0.112, SE, 0.054; p=0.044) was significantly associated with daily sedentary time after adjusting for all covariates. HGS, ALM, ALM/BMI, and ALM/weight were not significantly associated with daily sedentary time (Table 3).

Figure 1 illustrates the correlations between daily sedentary time and the skeletal muscle strength and mass parameters. Daily sedentary time was significantly correlated with HGS (r=-0.22, p<0.001), HGS/BMI (r=-0.20, p<0.001), HGS/weight (r=-0.19, p<0.001), ALM (r=-0.13, p<0.001), ALM/BMI (r=-0.16, p<0.001), and ALM/weight (r=-0.15, p<0.001).

Table 4 presents the β and SE values for the associations of daily sedentary time quartile with the skeletal muscle strength and mass parameters. Compared to the lowest quartile (Q1), the highest quartile (Q4) of daily sedentary time was significantly negatively associated with all skeletal muscle strength and mass parameters, except absolute ALM, in both adjusted models. Furthermore, a significant p for trend was observed for daily sedentary time quartile with respect to all skeletal muscle strength and mass parameters, apart from absolute ALM, in both adjusted models. This finding indicates the presence of a dose-response relationship. A higher daily sedentary time quartile was associated with greater reductions in skeletal muscle strength and mass parameters (Table 4).

Supplemental Material 1 depicts the correlation between the daily sedentary time quartile and the various skeletal muscle strength and mass parameters. A significant decreasing trend was observed across quartiles for all parameters: HGS (p for trend <0.001), HGS/BMI (p for trend <0.001), HGS/weight (p for trend <0.001), ALM (p for trend=0.002), ALM/BMI (p for trend <0.001), and ALM/weight (p for trend=0.002) (Table 4, Supplemental Material 1).

DISCUSSION

The association of sedentary time with skeletal muscle strength and mass was examined using data from a representative sample of United States adolescents aged 15 years to 19 years. All skeletal muscle strength and mass parameters, except for absolute ALM, were negatively associated with daily sedentary time, whether analyzed as a continuous variable or in quartiles. These associations persisted after adjusting for potential covariates, including PA. The results suggest that a sedentary lifestyle may be harmful to adolescents in terms of skeletal muscle strength and mass. However, the negative associations of daily sedentary time with HGS, as well as with ALM/weight, were not statistically significant in the vigorous PA group. In contrast, these associations remained significant in the groups characterized by moderate PA and no PA. This indicates that vigorous PA may mitigate the detrimental effects of a sedentary lifestyle on both skeletal muscle strength and mass. In a 2011 study, Martinez-Gomez et al. [17] explored the relationship between objectively measured PA and muscular fitness (MF), including HGS, in 211 Spanish adolescents from the AFINOS study using accelerometry. Their findings revealed that only vigorous PA was positively associated with MF. Furthermore, adolescents who engaged in higher levels of vigorous PA exhibited muscle strength comparable to those who participated in resistance training. These findings underscore the particular importance of vigorous PA over moderate or light physical activity (LPA) for adolescents, as reflected in various health guidelines that recommend vigorous PA for this age group [11,27].

To our knowledge, no research to date has demonstrated a negative association between sedentary time and skeletal muscle strength or mass in adolescents. However, a recent longitudinal study investigated the relationships of accelerometer-based sedentary time, LPA, and MVPA with fat mass. The participants, initially aged 11 years, were followed until they reached 24 years of age. The study found that each additional minute per day spent performing sedentary activities was associated with a 1.3-gram increase in fat mass. In contrast, each minute per day engaged in LPA and MVPA corresponded to a 3.6-gram and 1.3-gram reduction in fat mass, respectively, over the 13-year follow-up period [28]. Furthermore, cumulative sedentary time was found to be independently and directly associated with increases in both BMI and fat mass. In contrast, cumulative time spent in LPA to MVPA was associated with decreases in these measures [28]. The consistency between the longitudinal associations observed in this prior study and the cross-sectional associations in the present research suggests that sedentary behavior has harmful effects on the skeletal muscle health of youth.

While sedentary behaviors are distinct from physical inactivity, previous findings of lower PA in adolescents linked to poor skeletal muscle mass and strength may be comparable to the results of the present study. Many, but not all [29,30], studies have reported significant effects of PA on skeletal muscle mass and strength in adolescents [31-33]. Hao et al. [31] explored the relationships among PA, skeletal muscle mass, and diet in 640 American adolescents aged 14 years to 18 years from the LACHY study. They found that engaging in MVPA was associated with greater skeletal muscle mass (moderate PA: β, 0.19; p<0.001; vigorous PA: β, 0.15; p<0.001; MVPA: β, 0.20; p<0.001). A 2016 study by Ramires et al. [32] examined the associations of moderate and vigorous PA with lean and fat mass in 3176 Brazilian adolescents using data from a 1993 Pelotas birth cohort for a longitudinal investigation. In 2007, Foo et al. [33] demonstrated that consistent participation in PA during adolescence was associated with greater lean mass in Chinese boys (moderate PA: β, 0.40; p=0.004; vigorous PA: β, 0.95; p<0.001) and girls (moderate PA: β, 0.23; p=0.006; vigorous PA: β, 0.80; p<0.001); moreover, vigorous PA was associated with less fat mass in boys (β, -0.53; p=0.03) [34]. The associations between body composition, skeletal muscle strength, diet, PA, and total body and forearm bone mass were investigated in 283 Chinese adolescent girls aged 15 years in Beijing. Total PA level was significantly positively associated with HGS and lean body mass (p<0.001), suggesting that greater skeletal muscle strength and lean body mass may reflect higher PA levels [33].

Regarding skeletal muscle strength, Bim et al. [34] reported a relationship between HGS, PA, and sedentary behavior in a study of 971 Brazilian adolescents aged 15 years to 18 years. In boys, HGS was associated with PA (β, -0.114; p<0.001) and screen time-based sedentary behavior (β, -0.136; p<0.05), whereas those associations were not significant in girls. In another study, boys who accumulated over 80.7 minutes per day of MVPA exhibited a reduced probability of low physical fitness, including HGS (odds ratio [OR], 0.17; 95% confidence interval [CI], 0.06 to 0.47; p=0.001). For girls, just 8.4 minutes of vigorous PA daily was associated with a decreased likelihood of low fitness (OR, 0.23; 95% CI, 0.05 to 0.89; p=0.032). These results indicate sex differences in the relationship between PA and physical fitness in adolescents, suggesting that sex-specific PA guidelines may be necessary to improve physical fitness in this population [35].

Mechanism of the Influence of Physical Inactivity on Muscle Mass and Performance

Several biological pathways have been proposed to explain the observed association between sedentary behavior, PA, and the studied outcome variables. Sedentary behavior and PA are known to influence body composition, and their effects on muscle metabolism have been widely studied. Prior research involving older adults suggests that the relationships between habitual PA, sedentary behavior, and skeletal muscle strength likely stem from the detrimental physiological impacts of inactivity on health [36]. An overly sedentary lifestyle can lead to inadequate stimulation of the muscular endocrine system, which is involved in the production and secretion of myokines. This lack of stimulation can result in sarcopenia and frailty [36]. Furthermore, the disuse of skeletal muscles due to low PA and excessive sedentary behavior can lead to the accumulation of body fat and its infiltration into muscle cells, decreasing their stimulation and contraction power through endocrine and inflammatory mechanisms [37]. Extended periods of sedentary behavior can lead to insulin resistance, vascular dysfunction, a shift in substrate utilization toward carbohydrate oxidation, a transition in muscle fibers from oxidative to glycolytic, reduced cardiorespiratory fitness, and loss of muscle mass, strength, and bone mass. Additionally, prolonged sedentary time is linked to increased total body fat mass, visceral adipose tissue, blood lipid concentrations, and inflammation [38]. While sedentary behavior is known to disrupt the regulation of lipoprotein lipase activity by skeletal muscle mass, the pathophysiological mechanisms behind this disruption are not yet fully understood [38].

Strengths and Limitations

To our knowledge, this study is the first to evaluate the impact of daily sedentary time on HGS and ALM among United States adolescents using data from the NHANES. However, the study has several limitations. First, the cross-sectional nature of the data precluded the establishment of causal or temporal relationships. Longitudinal or interventional studies are thus needed to clarify the mechanisms underlying these associations. Second, the reliance on self-reported measures for sedentary behavior and MVPA introduces potential recall and reporting biases. Previous studies have used electronic accelerometers to mitigate these issues when assessing PA or sedentary behavior. Additionally, MET data derived from the International Physical Activity Questionnaire-Short Form are typically employed to quantify the intensity of PA; however, this method was not utilized in the present study. Thus, future research should incorporate accelerometry or MET calculations to obtain more accurate measurements. Moreover, despite using adjusted models with multiple covariates, residual confounding effects may still be present. Unmeasured covariates, such as nutritional status, could influence the observed relationships, but scarce data are available from large clinical trials using standardized dietary interventions [39]. Lastly, the results of this study are not generalizable to adolescent populations in other countries, as the data were sourced from the NHANES, which is specific to the American population.

This study identified a significant relationship of daily sedentary time with skeletal muscle strength and mass in a representative sample of United States adolescents of high school age. Specifically, HGS and ALM measures were found to be negatively associated with daily sedentary time. These findings underscore the need for targeted public health strategies and interventions to reduce sedentary behavior among adolescents, with the goal of improving overall physical health and preventing long-term consequences such as obesity, metabolic disorders, and musculoskeletal issues. Nevertheless, further research is needed to develop effective epidemiological strategies to combat the growing crisis of sedentary lifestyles in young people.

Supplemental Materials

Notes

Conflict of Interest

The authors have no conflicts of interest associated with the material presented in this paper.

Funding

This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (grant No. 2022R1A2C2010463, RS-2024-00338688). This study was supported by the Education and Research Encouragement Fund of Seoul National University Hospital.

Acknowledgements

None.

Author Contributions

Conceptualization: Oh KH, Min KB. Data curation: Oh KH, Seo K. Formal analysis: Oh KH. Funding acquisition: Min KB, Min JY. Methodology: Oh KH, Seo K, Min JY. Writing – original draft: Oh KH, Seo K. Writing – review & editing: Min KB, Min JY.

Figure. 1.

Correlations between daily sedentary time and various skeletal muscle strength and mass parameters. (A) HGS, (B) HGS/BMI, (C) HGS/weight, (D) ALM, (E) ALM/BMI, and (F) ALM/weight. BMI, body mass index.

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