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Table 1 Characteristics of analyzed original studies

From: Sedentary behaviors and anxiety among children, adolescents and adults: a systematic review and meta-analysis

Study Country Study design Population N (% of females) Mean age (SD) SB measure/indicator Anxiety measure Positive, negative or non-significant elation-ship between anxiety and the type of SB Main effects/findings Quality score (%)
Asfour et al., 2016 [59] USA Cross-sectional Adolescents; (general population) 575 (45%) 13.8 ± 0.64 years Time spent engaging in SB was calculated using five questions that inquired about time spent watching TV, playing video games, text messaging, Internet use and time spent on the telephone Internalizing symptoms subscale of 112-item The Youth Self-Report [60] 0 for ST Increased SB were associated with higher levels of externalizing symptoms (β = 2.03, SE = 0.32, p < .001), but not internalizing symptoms (β = 0.93, SE = 0.57, p = .1) 98
Asztalos et al., 2015 [61]a Belgium Cross-sectional Adults (general population) 4344 (52%) 43.55 ± 11.05 years Self-report - International Physical Activity Questionnaire (IPAQ) [62] 10-items for anxiety symptoms of Symptom Check List (SCL)(e.g. [63]) + for sitting time Sitting were positively associated with anxiety both in model adjusted for demographic (gender, age, education) (β = 0.037; p = .018) as well as adjusted for demographics and MVPA (β = 0.033; p = .038) 95
Bampton et al., 2015 [64]a Canada Cross-sectional Older adults (≥ 55 yr) (general population) 358 (66%) 66.5 ± 8.0 years Total and Domain Specific Measure of Sitting [5] Generalized Anxiety Disorder scale (GAD-2) [65] + for sitting time (+ for high sedentary time/low resistance group) Low sedentary time/high RT group reported lower anxiety symptoms compared to high sedentary time/low RT group (Mdiff = − 0.67, p = .001). The low sedentary time/low RT group reported lower anxiety symptoms than high sedentary time/low RT group (Mdiff = − 0.57, p = .018) 81
Cao et al., 2011 [66] China Cross-sectional Adolescents (general population) 5003 (48%) 13.13 ± 0.97 years Self-report to an open-ended question: how many hours per day, on average, the participants spent on the sedentary activities outside school hours on a usual weekday, as well as a weekend day (TV viewing, computer usage) [6]. ST was categorized as ≤2 h/d and > 2 h/d 41-item Screen for Child Anxiety Related Emotional Disorders (SCARED) [67] + for ST High screen time (> 2 h/day) was a risk factor for anxiety symptoms both in crude model (OR = 1.39, 95% CI: [1.22, 1.60], p < .001) as well as in adjusted for gender, grade, family type, perceived socioeconomic status, BMI, fruit and vegetable or fizzy drinks intake (OR = 1.36, 95% CI: [1.18, 1.57], p < .001) 95
de Wit et al., 2011 [68] Netherlands Cross-sectional Adults (general population) 2353 (65.45%) 41.2 ± 13.0 years Self-report - the daily number of hours a person spent on watching TV or computer use in leisure time Composite International Diagnostic Interview (CIDI, WHO ver. 2.1) [69] + for TV viewing; 0 for computer use Anxiety was related to spending more time watching TV (β = 0.051, p < .05; β = 0.103, p < .001, respectively) but not to time of computer use (β = 0.001, p = .971; β = 0.036, p = .155, respectively) in leisure time 82
de Wit et al., 2015 [70] Netherlands, Austria, Belgium, Ireland, Italy, Poland, Spain, UK, Denmark Cross-sectional Adult pregnant women (general population) 98 (100%) 31.6 ± 5.8 years Actigraph GT3X, GT1M or Actitrainer accelerometer [activity were calculated as time spent sedentary (< 100 cpm)] Pregnancy-related worries were measured with the 13-item Cambridge Worry Scale (CWS) [71] 0 for ASB Pregnancy-related worries were not significantly associated with sedentary behaviors 100
Dillon et al., 2018 [72] Ireland Cross-sectional Adults (general population) 397 (54%) 59.6 ± 5.5 A triaxial, GENEActiv accelerometer (ActivInsights Ltd., Kimbolton, Cambridgeshire, UK) Anxiety subscale of the 14-item Hospital Anxiety and Depression Scale [73] + for ASB Participants with moderate to severe anxiety symptoms had significantly more minutes of SB daily than those with low levels/ no symptoms of anxiety (p = .04) 100
Edwards & Loprinzi, 2016 [41] USA RCT Adults (general population) 39 (59%) Control: 22.08 ± 2.75; Intervention: 21.69 ± 2.71 GT9X accelerometers [21] and Digi-Walk SW-200 pedometer [74] Overall Anxiety Severity and Impairment Scale (OASIS) [75] + for ASB A statistically significant time x group interaction effect for OASIS scores F(1,37) = 11.13, p = .002). Mean and SE OASIS scores were significantly higher after the one-week sedentary behaviors-inducing intervention (M = 5.35, SE = 0 .86) compared to scores from before the intervention (M = 3.88, SE = 0.69) which means that an increase was observed in anxiety levels when participants increased their SB 89
Feng et al., 2014 [76]a China Cross-sectional Young adults (general population) 1106 (43%) 18.90 ± 0.9 years Self-report ST measured with one item: ‘How many hours per day do you spend on computer, including internet use, watching TV/video programs and playing games on a usual weekday and weekend day, respectively?’ The ST was categorized as ≤2 h/d and > 2 h/d Self-rating anxiety scale (SAS) [77] 0 for ST No statistically significant associations were found between ST and anxiety both for ≤2 h/day (OR = 1.52, 95% CI: [0.87, 2.64], p > .05) as well as for > 2 h/day ST levels 93
Gaskin et al., 2016 [78] Australia Cross-sectional Prostate cancer survivors (chronic illness) 98 with complete data; 49 with no complete data 67.3 ± 8.0 with complete data; 62.1 ± 8.6 with no complete data Hip-mounted ActiGraph GT1 M accelerometer (Pensacola, FL) units Memorial Anxiety Scale for Prostate Cancer (MAX-PC) – three subcales (prostate cancer anxiety, prostate-specific antigen anxiety, fear of recurrence) and a total anxiety scale [79] 0 for ASB Prostate cancer anxiety (B = 0.01, 95% CI: [− 0.03, 0.04], p = .78), prostate-specific antigen anxiety (B = 0.00, 95% CI: [− 0.00, 0.00], p = .96), fear of recurrence (B = − 0.01, 95% CI: [− 0.02, 0.01], p = .44) and a total anxiety (B = − 0.00, 95% CI: [− 0.05, 0.04], p = .94) were not significantly associated with SB 91
Gibson et al., 2017 [80]a United Kingdom Cross-sectional Adults (general population) 42 (55%) 38.0 ± 11.5 ActivPAL mini, an inclinometer-based activity monitor Anxiety subscale of The 14-item Hospital Anxiety and Depression Scale [73] + for ASB + for sitting time Those with < 8 h of SB per day on weekdays had significantly lower levels of anxiety compared with those who were sitting > 8 h or > 10 h per day. The main effect for weekday sitting time on anxiety (F(1, 41) = 3.05, p = .040, η2 = 0.18) 77
Gunnell et al., 2016 [81]a Canada Longitudinal Adolescents (general population) 1160 (61%) - Time 1 13.54 ± 1.12 years Self-report questionnaire - 6-items querying how many hours per day subjects typically engaged in TV viewing/video game playing/computer use). The first 3 items assess ST during weekdays and the last 3 items inquired about weekend days 10-items Multidimensional Anxiety Scale for Children-10 (MASC-10) [82] 0 for ST Initial symptoms of anxiety and ST did not predict change in ST and anxiety, respectively 95
Hiles et al., 2017 [83] Netherlands Longitudinal Adults (general population) 2932 (66%) at baseline 41.9 ± 13.1 Self-report single question – sedentary behavior as an average hours of sitting on a weekday. 21-item Beck Anxiety Inventory (BAI; [84]) 0 for anxiety- > sitting time change Anxiety at the baseline did not predict SB at a 2-year follow up (B = 0.02, p = .561) 100
Janney et al., 2013 [85]a USA RCT Adults with a diagnosis of schizophrenia/schizoaffective disorder with BMI > 27 (chronic illness) 46 (63%) 45.6 ± 9.8 years ActiGraph AM-7164 accelerometer (ActiGraph, Ft. Walton Beach, FL). Sedentary was established as ≤100 cpm PANSS (one item for anxiety) [86] 0 for ASB No association was observed between SB and PANSS psychiatric symptoms (PANSS or subscale: p ≥ .59). There were no significant associations for the PANSS questions asking about anxiety (rs = .22, p = .15 for sedentary minutes and rs = .15, p = .32 for percentage of sedentary time) 89
Kovess-Mastefy et al., 2015 [87] German, Netherlands, Lithuania, Romania, Bulgaria, Turkey Cross-sectional Schoolchildren (general population) 3184 8.72 years Parents were asked how long their child spends playing video games on average during the week. Low video game use was defined as 0–60 min per week; moderate use was defined as 61–300 min, and high use was > 300 min. GAD indexes of self-reported mental health computerized cartoon-like assessment tool ‘Dominic Interactive’ for children [88] 0 for video game playing Playing video games (1–5, and 5+ vs. 1 or less h) was not associated with GAD (OR = 1.08, 95% CI: [0.69, 1.7]; OR = 0.95, 95% CI: [0.53, 1.69], p > .05, respectively) 91
Kroeders et al., 2013 [89]a Australia Cross-sectional Stroke patients (chronic illness) 19 (53%) 66.2 ± 19.3 years PAL2 electronic device - dual axis accelerometer Anxiety subscale from Irritability, Depression and Anxiety (IDA) scale [90] - for sitting time Patients with anxiety symptoms compared with those without symptoms tended to spend more time lying (mean 64% vs. 43%), less time sitting (mean 33% vs. 51%), and less time standing or walking (mean 2% vs. 6%). The difference between these groups in time spent lying bordered on significance (t(17) = − 2.0; p = .06) 76
Liu et al., 2016 [91]a China Cross-sectional Secondary school pupils/adolescents (general population) 13,659 (49%) 15.18 ± 1.89 years The Youth Risk Behavior Survey (YRBS) questionnaire [92] ‘How many hours do you watch television or play VG/CU (including activities such as Nintendo, Game box, Xbox, computer games, and the internet) on a typical school day?’ The ST was categorized as: non-ST (0 h/day), occasional ST (> 2 h/day), moderate ST (> 1 to ≤2 h/day), high ST (> 2 h/day) The Multidimensional Anxiety Scale for Children (MASC) [82, 93] + for TV viewing; + for VG/CU time More than 2 h per school day of TV watching was associated with higher risk of anxiety in boys (OR = 1.43, 95% CI: [1.05, 1.95]) compared with no TV exposure. School day with high VG/CU time (> 2 h) was associated with higher risks of anxiety in boys (OR = 1.40, 95% CI: [1.061.86]) compared with no VG/CU 98
Maras et al., 2015 [94]a Canada Cross-sectional Adolescents (general population) 2482 (58%) 14.10 ± 1.57 years The Leisure-Time Sedentary Activities 6-item questionnaire measured how many hours per day subjects typically engage in: TV viewing/video game playing, computer use). The first 3 items assess screen-based activities during a typical weekday and the last 3 items screen time accrued on a typical weekend day. The Multidimensional Anxiety Scale for Children-10 (MASC-10) + for ST (hours per day of TV viewing; recreational computer use; video games); + for video game playing; 0 for TV viewing; 0 for computer Duration of screen time (β = 0.07, p < .001) and VG playing (β = 0.11, p < .001) was associated with severity of anxiety. 93
Mesquita et al., 2017 [95] Netherlands Prospective observational study Adults with COPD before/after pulmonary rehabilitation (chronic illness) 90 (40%) 67.0 ± 8.0 CIRO activity monitor (CAM or the MOX Activity Monitor (Maastricht Instruments B.V in Maastricht, the Netherlands) Anxiety subscale of the 14-item Hospital Anxiety and Depression Scale [73] 0 for anxiety- > ASB change Baseline anxiety levels were unrelated to changes in minutes of SB (pre-post rehabilitation, Spearman R = −.08 95
Opdenacker, & Boen, 2008 [96]a Belgium Longitudinal Adults (general population) 66 2 groups, aged M = 38.8 ± 11.4 years; and 39.9 ± 9.9 years Self-report - International Physical Activity Questionnaire (IPAQ) [62] The Spielberger state-trait anxiety inventory (STAI) [21] 0 for sitting time Sitting time was not associated with anxiety (r = 0.46, p = .623). 85
Padmapriya et al., 2016 [97]a Singapore Cross-sectional Pregnant women (general population) 257 with state anxiety symptoms; 270 with trait anxiety symptoms 29.5 ± 5.7 with state anxiety symptoms; 29.5 ± 5.6 with trait anxiety symptoms Two categories of self-reported total sitting time per day and TV viewing time per day: < 7 h of total sitting time per day and < 2 h of TV viewing time per day were identified as lower tertiles; ≥7 h of total sitting per day and ≥ 2 h of TV viewing time per day were defined as higher total sitting time and TV time The Spielberger state-trait anxiety inventory (STAI) + for TV viewing Women with higher TV viewing time had higher state anxiety compared to women with lower TV viewing time in crude analysis (OR = 1.56, 95% CI: [1.14, 2.14], p = .006) 95
Park et al., 2017 [98]a United Kingdom Cross-sectional Older adults (residents from assisted living facilities), (chronic illness) 87 77.5 ± 8.2 Accelerometers (GT3X+, WGT3X-BT; ActiGraph (Pensacola, FL, USA) Anxiety subscale of the 14-item Hospital Anxiety and Depression Scale [73] - for ASB SB was negatively associated with anxiety (r = −.39, p < .01) 95
Rebar et al., 2014 [99]a Australia Cross-sectional Adults (general population) 1104 (55%) 58 (range 48–66) 10-item Workforce Sitting Questionnaire [100] Anxiety subscale from 21-item Depression, Anxiety, and Stress Scale (DASS-21) [101] + for overall sitting time + for computer sitting 0 for leisure/work/TV sitting Overall sitting time (b = 0.03, p < .05) and computer use (b = 0.03, p < .05) were significantly associated with anxiety. Leisure (b = 0.01, p > .05), work (b = 0.02, p > .05), and TV (b = 0.00, p > .05) were not associated with anxiety 100
Sanchez-Villegas et al., 2008 [102] Spain, USA Longitudinal Adults (general population) 10,381 27 years Self-report sedentary index: hours per week spent on watching television and/or using computer. Self-reported anxiety: ‘Have you ever been diagnosed of anxiety by a health professional?’ - classified as an incident case of anxiety 0 for ST There was no significant association between the sedentary index and anxiety risk (p = .17) 89
Straker et al., 2013 [103]a Australia Longitudinal Adolescents (general population) 643 (54%) 14.0 ± 0.2 years Screen Based Media – Self-report recall electronic diary/questionnaire MARCA - clusters: C1. instrumental computer gamers; C2. multi-modal e-gamers; C3. computer e-gamers [104] Internalizing symptoms index of 112-item the Youth Self-Report [59] + for game playing C1 males reported less internalizing behavioral problems than C2 (difference − 1.7, 95% CI: [− 3.5, 0.1], p = .065) or C3 males (difference − 2.6, 95% CI: [− 4.9, − 0.3], p = .027) 91
Teychenne & Hinkley, 2016 [105]a Australia Cross-sectional Adult women with children aged 2–5 years (general population) 575 (100%) 37.18 ± 4.62 years Self-report –of women’s own activities, including time spent on TV/DVD/video viewing, computer/e-games/hand held device use on a typical weekday and weekend day 7-items related to symptoms of anxiety experienced in the past week: a subscale (HADS-A) of the Hospital Anxiety and Depression Scale (HADS) [106] + for computer /device use + for total ST; 0 for TV viewing TV viewing was not associated with anxiety symptoms (B = 0.109, p = .188) but computer/device use (B = 0.212, p = .011) and overall screen time (B = 0.109, p = .025) were positively associated with heightened anxiety symptoms in models adjusted for key demographic and behavioral covariates (including MVPA) 100
Uijtdewilligen et al., 2011 [107] Netherlands Longitudinal Adolescents (general population) 217 (58%) M: 13.0 ± 0.6 years; F: 12.9 ± 0.6 years Acti-Graph accelerometers (Model GT1M, ActiGraph, LLC, Fort Walton Beach, FL) Facilitating anxiety index of Achievement Motivation Test (AMT) [108] + for ASB In males, a higher score on facilitating anxiety (B = 5.13, 95% CI: [0.08, 10.19], p < .05) was associated with more minutes spent sedentary in adulthood. 88
Vallance et al., 2015 [109]a Canada; Australia Cross-sectional Adults (general population) 197 (overall 180–45%) 64.3 ± 10.3 Acitgraph GT3X+ accelerometer (Actigraph, LLC, Pensacola, FL) Spielberger’s State Anxiety Inventory (STAI) - 10 items 0 for ASB No significant associations emerged for sedentary time and psychological health outcomes (including anxiety) [Wilks’ λ = 0.956, F(9382.3) = 0.788, p = .628] 93
van Roekel et al., 2016 [110]a Netherlands Cross-sectional Adults treated for stage I–III colorectal cancer (chronic illness) 145 (37.2%) 70.0 ± 8.7 years The triaxial MOX activity monitor (MMOXX1, upgraded version of the CAM monitor) Anxiety subscale of the 14-item Hospital Anxiety and Depression Scale [73] 0 for ASB (0 for sedentary per 1 h/day) Substituting sedentary time with physical activity was not significantly associated with lower anxiety (β = −0.7, 95% CI: [− 1.7, 0.3]) 95
Vancampfort et al., 2018 [111] China, Ghana, India, Mexico, Russia, South Africa Cross-sectional Adults (general population) 42,469 (50.1%) 43.8 ± 14.4 Self-report sitting time – total time usually spent (expressed in minutes per day) sitting or reclining including at work, at home, getting to and from places, or with friends (e.g., sitting at a desk, sitting with friends, travelling in car, bus, train, reading, playing cards or watching television) Self-reported anxiety by the question ‘Overall in the past 30 days, how much of a problem did you have with worry or anxiety’ with response alternatives: none, mild, moderate, severe, extreme. Those who answered severe or extreme were considered to have anxiety + for sitting time Anxiety was significantly associated with higher mean time spent sitting (b = 24.16, 95% CI: [6.95, 41.38], p < .01) 100
Wu et al., 2015 [112] China Cross-sectional Adults (general population) 4747 (58.4%) - 16.3% with anxiety 19.2 ± 1.41 years Self-report screen time measured with one item: ‘How many hours per day do you spend on the computer (including playing video or computer games or computer for something) and watching TV/video programs on a usual weekday and weekend day, respectively?’ ST was categorized as ≤2 h/d and > 2 h/d Self-rating anxiety scale (SAS) [77] + for ST High screen time > 2 h/day (OR = 1.38, 95% CI: [1.15, 1.65], p < .001) was significantly positively associated with anxiety in crude model as well as in a model adjusted for gender, age, residential background, BMI, perceived family economy and perceived study burden (OR = 1.49, 95% CI: [1.24, 1.79], p < 0.001) 98
  1. ASB accelerometry measured sedentary behaviors, SB sedentary behaviors (three article which provided broad definition of obtained sedentary behaviors index), ST total screen time, MVPA moderate-to-vigorous physical activity, RT resistance training, VG video games, CU computer use, GAD generalized anxiety disorder
  2. astudies included into meta-analysis