Relationship between smartphone addiction and physical activity in Chinese international students in Korea

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The hierarchical regression models showed increasing predictive power, with R2 increasing from 30.3% to 72.5%, and each block had significant explanatory value.

“The changes in R2 showed that predictive power improved whenever the other variables were added to the model. Consequently, the % of variability increased from 30.3% to 72.5%. Each Block represented significant explanatory values to the level of smartphone addiction (F(5, 104) = 8.848, p < 0.001, F(7, 102) = 19.869, p < 0.001, F(9, 100) = 28.648, p < 0.001, respectively).”

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The high-risk addiction group averaged roughly 4,000 daily steps and showed greater fat mass and less muscle mass than those averaging about 8,000 steps.

“Our study also showed that subjects with high-risk smartphone addiction took an average of 4,000 steps per day and had higher fat mass and lower muscle mass, compared to participants taking an average of 8,000 steps per day.”

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Among 110 Chinese international students, 60.0% were no-risk, 20.9% potential-risk, and 19.1% high-risk smartphone users based on SAPS.

“Based on the evaluation by the SAPS, 60.0% (n = 66; 34.63 ± 3.55) were no-risk smartphone users, 20.9% (n = 23; 41.43 ± 0.99) were potential-risk smartphone users, and 19.1% (n = 21; 46.24 ± 3.22) were high-risk smartphone users.”

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There were significant differences in muscle mass, fat mass, average daily walking steps, and average daily consumed calories across smartphone addiction levels.

“On the other hand, there were significant differences in muscle mass, fat mass, average number of walking steps per day, and the average consumed calories per day.”

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Fat mass was significantly higher in high-risk smartphone users than in lower risk levels (p < 0.001), and positively correlated with smartphone addiction level (r = 0.435, p < 0.001).

“Contrarily, fat mass for high-risk smartphone users was significantly higher than subjects with lower risk levels (p < 0.001), and it was in proportion to the level of smartphone addiction (r = 0.435, p < 0.001).”

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Average daily walking steps and average daily consumed calories were significantly lower in high-risk addiction participants (all ps < 0.001), with negative correlations with smartphone addiction level (rs = −0.798 and −0.578, respectively, ps < 0.001).

“The average number of walking steps and average consumed calories per day in subjects with high-risk addiction were significantly lower (all ps < 0.001), resulting in a significant negative relationship (rs = −0.798 and −0.578, respectively, ps < 0.001).”

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  “In this study, participants with high-risk smartphone addiction had a significantly lower average number of walking steps and consumed calories per day.”

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Muscle mass was significantly lower in high-risk smartphone addiction participants than in no-risk and potential-risk participants (p = 0.001), and inversely correlated with smartphone addiction level (r = −0.245, p = 0.010).

“Specifically, the muscle mass of participants with high-risk smartphone addiction was significantly lower than those with no-risk and potential risk (p = 0.001), and muscle mass was in inverse proportion to the level of smartphone addiction (r = −0.245, p = 0.010).”

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The study did not provide additional data on stress, self-efficacy, impulsivity, depression, social support, or physical health conditions.

“Finally, no additional information including the effect of stress, self-efficacy, and impulsivity on smartphone addiction, depression, social support, and their physical health conditions was provided.”

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More smartphone time and fewer daily steps in addicted participants may lower energy expenditure, possibly reducing muscle mass and raising fat mass.

“These results suggest that subjects with smartphone addiction spent more time using their smartphones and were involved in less walking each day, resulting in lower energy expenditure, which may contribute to reducing muscle mass and increasing fat mass.”

• AssumptionRests on an assumption: The body composition differences (higher fat mass and lower muscle mass) are caused by lower physical activity and energy expenditure rather than other factors.

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Those walking under 5,000 steps daily showed higher cardiometabolic risk prevalence than those walking more.

“Schmidt, Cleland, Shaw, Dwyer and Venn (2009) reported that people taking less than 5,000 steps per day had a significantly higher prevalence of cardiometabolic risk than those totaling more steps per day.”

• cites Schmidt et al., 2009Not checked yet

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A 3-day measurement period is enough to estimate physical activity.

“Tudor-Locke et al. (2005) suggested that measurement during any 3 days can provide a sufficient estimate for physical activity.”

• cites Tudor-Locke et al., 2005Not checked yet

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Multicollinearity was examined using VIF statistics, with VIF values between 2.190 and 6.716.

“multicollinearity was examined using Variance Inflation Factor (VIF) statistics (2.190 ≤ VIF values ≤ 6.716).”

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Guidelines equate recommended moderate-to-vigorous activity with 7,100-11,000 daily steps.

“The recommended moderate-to-vigorous physical activity is equivalent to 7,100 to 11,000 steps per day.”

• cites Tudor-Locke et al., 2011Not checked yet

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The SAPS has been reported as a valid and reliable screening tool for adolescent smartphone addiction risk, with Cronbach's α = 0.814.

“The SAPS used in this study was developed by the National Information Society Agency (Shin, Kim & Chung, 2011), which has been reported to be a reliable and valid diagnostic scale for screening adolescents who may be at risk of smartphone addiction (Cronbach’s α coefficient = 0.814) (Kim et al., 2014; Shin et al., 2011).”

• cites Kim et al., 2014Not checked yet

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• cites Shin et al., 2011Not checked yet

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Lower daily walking was linked to smartphone addiction, and this may damage health through greater fat mass and reduced muscle mass.

“Namely, smartphone addiction was associated with less physical activity, such as daily walking, and consequently may be harmful to physical health by resulting in higher fat mass and decreasing muscle mass induced by less physical activity.”

• AssumptionRests on an assumption: The observed association between smartphone addiction and lower physical activity reflects a causal effect of smartphone addiction on physical activity rather than reverse causation or confounding.
• AssumptionRests on an assumption: The body composition differences (higher fat mass and lower muscle mass) are caused by lower physical activity and energy expenditure rather than other factors.

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For health maintenance, adults require either 30 minutes of moderate aerobic exercise five days weekly or 20 minutes of vigorous exercise three days weekly.

“All healthy adults need moderate-intensity aerobic activity for a minimum of 30 minutes, five days a week or vigorous-intensity aerobic activity for a minimum of 20 minutes, three days a week to enhance and maintain health (Haskell et al., 2007).”

• cites Haskell et al., 2007Not checked yet

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Women who walked 5,000-7,500 steps daily had lower BMI than women walking under 5,000 steps daily.

“Women taking 5,000~7,500 steps per day had a significantly lower BMI than those taking less than 5,000 steps per day (Krumm, Dessieux, Andrews & Thompson, 2006).”

• cites Krumm et al., 2006Not checked yet

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Increased hours of smartphone usage and fewer daily walking steps are potential risk factors for smartphone addiction.

“These results suggested that increased hours of smartphone usage and less walking steps per day constituted the potential risk factors of smartphone addiction.”

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Findings may not generalize beyond Chinese international students, a small sample, and individuals in their early twenties.

“First, the generalizability of the findings may be limited because participants of this study were confined to Chinese international students and the sample size was small. Moreover, this study only focused on subjects in their early twenties.”

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Cell phone use was reported to interfere with leisure-time activity, increase sedentary behavior, and lower cardiorespiratory fitness such as peak oxygen consumption.

“Lepp et al. (2013) also reported that cell phone use disrupted leisure time physical activity, promoting sedentary behaviors and reduced cardiorespiratory fitness, like peak oxygen consumption.”

• cites Lepp et al., 2013Not checked yet

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Smartphone addiction could harm physical health by lowering activity, increasing fat mass, and decreasing muscle mass, with adverse health consequences.

“Namely, smartphone addiction may negatively influence physical health by reducing the amount of physical activity, such as walking, resulting in an increase of fat mass and a decrease of muscle mass associated with adverse health consequences.”

• AssumptionRests on an assumption: The observed association between smartphone addiction and lower physical activity reflects a causal effect of smartphone addiction on physical activity rather than reverse causation or confounding.
• AssumptionRests on an assumption: The body composition differences (higher fat mass and lower muscle mass) are caused by lower physical activity and energy expenditure rather than other factors.

Probably not a substantial claim: may not pass S3 (load-bearing).

Among Chinese smartphone users, low Internet self-efficacy, positive outcome expectancies, and high impulsivity were identified as possible risk factors for social networking site addiction.

“Wu, Cheung, Ku and Hung (2013) reported that low Internet self-efficacy, positive outcome expectancies, and high impulsivity were verified as potential risk factors of addictive tendencies toward social networking sites among Chinese smartphone users.”

• cites Wu et al., 2013Not checked yet

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