Journal of Physical Activity and Health, 2015, 12, 1112 -1118 http://dx.doi.org/10.1123/jpah.2013-0513 © 2015 Human Kinetics, Inc.
ORIGINAL RESEARCH
Cross-Sectional Associations Between Sitting Time and Several Aspects of Mental Health in Belgian Adults Melinda Asztalos, Greet Cardon, Ilse De Bourdeaudhuij, and Katrien De Cocker Background: Sedentary behavior (including sitting) is negatively associated with physical health, independent from physical activity (PA). Knowledge on the associations with mental health is less elaborated. Therefore this study aims to investigate the relationship between sitting and 5 indices of mental health in adults (psychological distress, depression, anxiety, somatization, and sleeping problems), and between sitting interactions (sitting×gender, sitting×age, sitting×education, and sitting×PA) and these mental health indices. Methods: A cohort of Belgian adults (25–64 years; n = 4344) provided self-reported data on sitting and PA and on 5 mental health indices. Cross-sectional associations were examined using multiple linear regression analyses. Results: Analyses adjusted for gender, age, education, and PA showed significant positive associations between sitting and the 5 mental health indices (P < .05). All associations were true for both men and women, and for low and high educated individuals, while some were only found in older individuals (somatization, P < .001) and those being insufficiently active (psychological distress, P = .007; depression, P = .002; and anxiety, P = .014). Conclusions: More sitting seems to be associated with poorer mental health, independently of gender, age, education, and PA. Moderation analyses showed that these associations may differ according to age and PA levels. Keywords: sedentary behavior, survey, cross-sectional study, regression analysis
There is a solid base of scientific evidence supporting the major impact of physical activity (PA) on human physical1–3 and mental health.4–6 Recently, attention toward the independent health risks of sedentary behaviors (waking activities characterized by energy expenditure ≤ 1.5 MET in sitting or reclining posture)7 started to grow. A significant body of work in this area has been published, emphasizing that sedentary behavior is a distinctive form of human behavior that should not be considered the endpoint of the PA continuum.8 Accordingly, among the individuals who fulfill PA recommendations many may actually be just as sedentary as their inactive counterparts, and therefore, it is important to identify the health risks of actual sedentary time.9,10 The currently growing knowledge-base on the independent health outcomes of sedentary behavior shows strong associations with risks for all-cause-mortality and cardio-vascular mortality risks,11 as well as for various other chronic diseases such as diabetes, cancer, obesity, hypertension, and bone/joint-disease.10,12 Knowledge on the potential outcomes of sedentary behavior on mental health is less extensive, but starting to grow, with evidence suggesting a negative association between sedentary behavior and mental health.13–17 As mental health disorders are commonly occurring,18,19 more research on this topic is needed. In most of the previous studies only depression13,16,17 or a general mental health score14,15 were used as outcomes, while other mental health problems, such as anxiety and psychological distress are also common in the general population.20 For example, in Belgium 6% of the adult population suffers from anxiety, 8% from depression, 8% from somatization, 20% from sleeping problems, and 24% from psychological distress.21
As a result, research is needed on the association between sedentary time and a diversity of mental health indices. In addition, the influence of demographic variables, such as age, gender, and education, should be included as these were found to be related to mental health in general22,23 or were important in the PA–mental health relationship.5,6 For example, sports participation was related to less psychological distress in unemployed midaged adults, and to less perceived stress in unemployed women, unemployed young adults, and young adults with blue-collar jobs. Moreover, as previous research also showed that PA is related to mental health, and as the association between moderate-to-vigorous intensity PA (MVPA) and sedentary behavior may be high for some people but low for others, it is important to also include PA when studying the relationship between sedentary behavior and mental health. Consequently, the first aim of the current study was to analyze the relationship between sedentary time (defined here as sitting time) and 5 different mental health indices in adults, independent of gender, age, education, and PA. The hypothesis is that sitting time will be independently positively associated with psychological distress, depression, anxiety, somatization and sleeping problems. The second aim of the study was to test the associations of sitting time interaction terms (with age, gender, education and MVPA) with the mental health indices. It is hypothesized that the associations between sitting time and the mental health indices will differ according to the demographic (similar to some PA-mental health association) and PA variables.
Methods Study Design
The authors are with the Dept of Movement and Sports Sciences, Ghent University, Gent, Belgium. De Cocker ([email protected]) is corresponding author. 1112
The Belgian Health Interview Survey (B-HIS) aims at giving a description of the health status of the population by identifying health problems, describing health needs, analyzing social trends in the health status, and estimating the prevalence and distribution
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of health indicators.24 For the B-HIS, a multistage sampling design was applied involving a geographical stratification, a selection of clusters, a selection of household within each cluster and a selection of respondents within each household. Copies of the National Population Registry were used as the sampling frame. Invitation letters attached to informative leaflets were sent to the households of the selected individuals. Afterward, trained interviewers contacted the households’ members and explained them the objectives of the survey, obtaining their informed consent for cooperation. Data were collected through a face-to-face interview at the respondents’ home. Additional details about this multistage sampling procedure are available in the B-HIS report.24,25 With a response rate of 61.4% at household level (ie, 5530 households), the B-HIS included a total of 12,111 participants (51.1% women and 48.9% men), covering all ages from infants to 99-year-old individuals (0–24 years: n = 3254; 25–64 years: n = 6720; 65–99 years: n = 2137). The B-HIS sample has a similar gender and age distribution as the Belgian population,26 but was higher educated than the Belgian population.27 Reasons for refusing participation per household were: lack of time (22.1%), lack of interest (38.3%), old age and/or disease (6.7%), and other/unspecified reasons (32.7%) (see Figure 1). The protocol of the B-HIS was approved by the Ethical Committee of the Belgian Scientific Institute of Public Health.
Participants From the original total sample, 4344 adults (64.6% of all 25- to 64-year-olds) provided data on both sitting and mental health and
were consequently included in this study. The group of nonrespondents had the same age as the study sample, but included more men (52.6%, P < .001) and more lower educated (no diploma, primary, and lower secondary education) individuals (33.0%, P < .001) than the study sample included here.
Measurements The instruments used in this study were part of the face-to-face form of the B-HIS, which was constructed following strict protocols,24,25 and provided demographic information as well. The demographics included gender, age, and education (no diploma, primary, lower secondary, higher secondary, and higher education). International Physical Activity Questionnaire (IPAQ). The IPAQ is a valid measure for monitoring population levels of PA and sitting among 18- to 65-year-old adults in diverse settings, capturing all facets of PA (eg, transportation, occupation, household, and leisure), and sitting (eg, reading, television viewing and sitting at a desk). The IPAQ produced repeatable data (Spearman’s rho clustered around 0.8), with a criterion validity median ρ of about 0.30.28 The short, last week version of the IPAQ, particularly suitable for use in largescale surveys, was used in this study. Four questions in the IPAQ asked participants to report separately hours and minutes spent sitting on a weekday and on a weekend day during the last week. Based on participants’ reports, weekly total minutes of sitting were computed: [(weekday hours × 60) + weekday minutes] × 5 + [(weekend day hours × 60) + weekend day minutes] × 2.
Figure 1 — Flowchart B-HIS study. JPAH Vol. 12, No. 8, 2015
1114 Asztalos et al
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The IPAQ supplied also information about PA during the last week. Participants reported the following for moderate-intensity PA and vigorous-intensity PA: number of days of the last week engaged in this PA, hours engaged in this PA during 1 of those days, and minutes engaged in this PA during 1 of those days. Total minutes spent in moderate-to-vigorous intensity PA (MVPA) were computed, according to established methods posted on the IPAQ website (https://docs.google.com/viewer?a=v&pid=sites&srcid= ZGVmYXVsdGRvbWFpbnx0aGVpcGFxfGd4OjE0NDgxMDk3 NDU1YWRlZTM). General Health Questionnaire (GHQ). The first mental health index, psychological distress, which referred to overall psychological discomfort, was assessed using official translations of the GHQ.29 The GHQ is a well-established psychological screening instrument, assessing participants’ current state, and asking whether it differs from their usual state.30,31 It focuses on the inability to carry out normal functions, and the appearance of new and distressing psychological phenomena. The 12-item GHQ, used in the current study, asked about participants’ recent experiences, feelings, and thoughts (eg, Have you recently been able to concentrate on whatever you were doing?). Answer categories were on a 4-point response scale (not at all / same as usual / more than usual / much more than usual), and the bimodal scoring method was applied (ie, 0 = not at all or same as usual, 1 = more than usual or much more than usual), as this is the original scoring method.32 GHQ12 total scores were obtained by summing across all items, after reversing responses to the 6 positively stated items. Total scores ranged from 0 to 12, with higher scores indicating more psychological distress. A score of minimum 4 is known to indicate high levels of psychological distress. Cronbach’s alpha for the 12 items was 0.89 in the present sample. Symptom Check List (SCL). The other 4 mental health dimensions are feelings of depression or anxiety, symptoms of somatization, and sleeping problems, all deriving from an official translation of the SCL.33 The SCL is a widely used, valid, and reliable selfreport symptom inventory that provides an overview of a person’s symptoms and their intensity at a specific point in time (ie, last week including the day of the interview).34,35 The following 42 items (of the 90 items in the total SCL) were used in the current study: 17 items for depression (Cronbach’s α = .94) (eg, Did you cry easily in the last week, today included?), 10 items for anxiety (Cronbach’s α = .91) (eg, Did you feel nervous or shaking inside in the last week, today included?), 12 items for somatization (Cronbach’s α = .88) (eg, Did you experience chest pain in the last week, today included?), and 3 items for sleeping problems (Cronbach’s α = .80) (eg, Did you have difficulties falling asleep in the last week, today included?). Answer categories were on a 5-point Likert scale, ranging from 0 = not at all to 4 = extremely (ie, 1 = a little bit, 2 = moderately, 3 = quite a bit). Scores of 0 to 1 represent a low score of the mental health outcome and 2-3-4 stand for a high score.
health indices and of sitting with the covariates. Before conducting the multiple regressions, bivariate correlation coefficients between the independent variables were calculated to test for multicollinearity. Secondly, multiple linear regression analyses were used including sitting interaction terms (sitting×gender, sitting×age, sitting×education, and sitting×MVPA) (moderated multiple regressions) to test the statistical significance of these terms in their association with mental health dimensions. Again, 2 models were developed: one adjusted for gender, age, education, and sitting (model used for sitting×gender, sitting×age, sitting×education), and one additionally adjusted for MVPA (model used for all interactions). In case the interaction term showed to be a significant predictor, the association between sitting and mental health dimensions was assessed in 2 groups (based on the median value of the moderator) via stratified analysis. All analyses were done with SPSS 19 for Windows and standardized regression coefficients were reported. For all analyses, statistical significance was set at 0.05.
Results Table 1 presents the demographics, mental health, sitting time and MVPA scores of the individuals in the study sample. Mean age of the sample was 43.55 (SD = 11.05) years and respondents sat on average for 4.71 (SD = 2.30) hours/day. The majority was higher educated and had low scores for the mental health indices. Sitting time and the covariates were significantly associated with the mental health indices and sitting time was associated with the covariates (P < .05, data not shown). Coefficients between the Table 1 Participants Characteristics Demographics Gender: men, n (%) Age Mean (SD) years
43.55 (11.05)
Young adults (24–43 years): n (%)
2269/4344 (52.2)
Education: n (%) No diploma
58/4255 (1.4)
Primary education
391/4255 (9.2)
Lower secondary education
767/4255 (18.0)
Higher secondary education
1373/4255 (32.3)
Higher education
1666/4255 (39.2)
Mental health: mean (SD); % high score
Statistical Analyses For the first aim, multiple linear regression analyses were conducted to examine the association between sitting (predictor variable) and 5 mental health dimensions (dependent variables). Two different models were developed: 1) adjusted for demographics (gender, age, education) and 2) adjusted for demographics and MVPA. First bivariate linear regressions were conducted to test the associations of sitting and the covariates with the mental
2075/4344 (47.8)
Psychological distressa
1.30 (2.37); 13.4
Depressionb
1.30 (0.48); 1.8
Anxietyb
1.27 (0.47); 1.8
Somatizationb
1.34 (0.44); 1.2
Sleeping problemsb
1.64 (0.83); 9.9
Sitting: mean (SD) hours/day
4.71 (2.30)
MVPA: mean (SD) minutes/day
56.80 (84.41)
Score between 0–12; score ≥ 4 is considered a high score. Score between 0–4; score ≥ 2 is considered a high score. Abbreviations: MVPA, moderate-to-vigorous intensity physical activity. a
b
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independent variables were no higher than 0.60 (data not shown), so multicollinearity was not a problem in this study. Table 2 (see aim 1) gives an overview of the associations (beta and P-values of the controlled multiple regressions) between sitting and 5 mental health dimensions. In both models, sitting is positively associated (P < .05) with psychological distress, depression, anxiety, somatization and sleeping problems. The second aim was to look at the associations of sitting interactions (sitting×gender, sitting×age, sitting×education and sitting×MVPA) and the mental health dimensions (see Table 2, aim 2). For the sitting×gender interactions, no significant associations were found with the mental health dimensions. For age, a significant association was found between the sitting interaction
term (sitting×age) and somatization in the 2 adjusted models. Post hoc analyses stratified by age (split at median age) revealed that the association between sitting and somatization is not significant for young adults (< 43 years), while it is positive for older adults (> 43 years) (β = 0.084, P < .001). The associations between sitting*age and the other mental health dimensions were not significant. The interactions of sitting with education showed no significant associations with mental health. The interaction sitting×MVPA was significantly associated with psychological distress, depression and anxiety. Post hoc analyses stratified by MVPA showed that the associations between sitting and the 3 mental health dimensions were not significant for those reporting more than 30 minutes of MVPA daily, while for those
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Table 2 Associations Between Sitting and Mental Health and Between Sitting Interactions and Mental Health Model 1a Independent
Dependent
Model 2b
𝛃c
P
𝛃c
P 0.002
Aim 1 Sitting (ST)
Psychological distress
0.050
0.001
0.051
Depression
0.049
0.002
0.047
0.004
Anxiety
0.037
0.018
0.033
0.038
Somatization
0.045
0.004
0.042
0.008
Sleeping problems
0.043
0.006
0.044
0.006
Psychological distress
0.035
0.382
0.040
0.319
Aim 2 ST×gender
ST×age
ST×education
ST×MVPA
Depression
0.064
0.104
0.068
0.088
Anxiety
0.008
0.849
0.014
0.733
Somatization
0.015
0.701
0.014
0.731
Sleeping problems
0.014
0.722
0.019
0.631
Psychological distress
–0.005
0.950
–0.021
0.788
Depression
0.000
0.996
–0.012
0.873
Anxiety
0.026
0.727
0.015
0.841
Somatization
0.218
0.003
0.213
0.005
Sleeping problems
0.080
0.291
0.081
0.293
Psychological distress
0.003
0.946
0.002
0.976
Depression
0.019
0.705
0.012
0.821
Anxiety
0.038
0.451
0.035
0.488
Somatization
0.043
0.387
0.033
0.517
Sleeping problems
0.062
0.226
0.068
0.198
Psychological distress
–0.081
0.019
Depression
–0.098
0.004
Anxiety
–0.071
0.038
Somatization
–0.014
0.668
Sleeping problems
–0.043
0.211
Abbreviations: ST, sitting; MVPA, moderate-to-vigorous intensity physical activity. a Adjusted for gender, age and education. b Aim 1 adjusted for gender, age, education, and MVPA; aim 2 adjusted for gender, age, education, MVPA, and sitting. c Standardized coefficients. Note. Bold surfaces indicate statistically significant associations (P < .05). JPAH Vol. 12, No. 8, 2015
1116 Asztalos et al
reporting less than 30 minutes of MVPA per day, sitting was positively associated with psychological distress (β = 0.065, P = .007), depression (β = 0.074, P = .002) and anxiety (β = 0.059, P = .014). No significant associations were found between the interaction sitting×MVPA and somatization or sleeping problems.
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Discussion Because sedentary behavior research is at a stage requiring more in-depth investigations of potential mental health outcomes, the current study examined the relationship between sitting and 5 mental health dimensions in a national cohort of 4344 Belgian adults, aged 24 to 65 years. Variations across gender, age, education, and participation in MVPA in these associations were also investigated which is fairly new to the literature. The results provided evidence of the independent, positive association between sitting and the 5 mental health dimensions that were investigated (psychological distress, depression, anxiety, somatization, and sleeping problems), as analyses were controlled for demographics and MVPA. The first hypothesis (more sitting time is independently associated with poorer mental health) is hereby confirmed. Subsequent moderation analyses, testing the significance of the sitting interaction terms, found that these associations were present in both gender and both education groups. However, some of the associations of sitting with the mental health outcomes differed between both age groups and between both PA groups. The positive association between sitting and somatization was nonexistent among younger individuals and sitting was not associated with psychological distress, depression, and anxiety among those participating in MVPA. More research is needed to find out if and which other factors associated with age or PA are responsible for these findings. No other studies were found examining the association between overall sitting and several mental health dimensions, as was done in this study. However, 2 studies looking at domain-specific sitting also found associations with overall mental health. A Dutch study showed that sitting during leisure time and particularly TV viewing was associated with poorer mental health in the working population.14 Sitting during transport and sitting at work on the other hand were not associated with mental health in this crosssectional population based study of 20- to 59-year-old adults.14 In a prospective study in Spanish university graduates, those with the highest level of TV viewing and computer use showed an increased risk (31%) of developing mental health problems compared with those reporting less time in these sedentary activities.15 Furthermore, several studies looked at the association between overall sitting36,37 or domain-specific sitting,13,16,38,39 and 1 particular mental health dimension, namely depressive symptoms (while the current study looked at 5 mental health dimensions). Cross-sectional studies showed that depression was positively associated with overall sitting in Los Angeles adults36 and in 18- to 55-year-old overweight and obese women in San Diego;37 with Internet use in American households;38 with computer use, screen time, and overall sitting in 18- to 45-year-old women from Australian disadvantaged neighborhoods;13 and with leisure time computer use in 18- to 65-year-old Dutch adults.17 One longitudinal study examining the association between media use in adolescence and depression in young adulthood, revealed that more TV use had significantly greater odds of developing depression.16 The positive association between overall sitting time and depression found in the current study is in line with these previous results. Only some studies looked at joint associations between sitting and demographics or PA on mental health. In the study of Proper
and colleagues,14 working status and weight status showed to be modifiers in the associations between sitting and mental health. The findings of Sanchez-Villegas et al15 suggest that among those with lower PA levels, TV and computer use might have an import role in the incidence of anxiety, while for those with higher PA levels, these behaviors seem not to be so important. Our results show the same for anxiety, and also for psychological distress and depression. Teychenne et al13 on the other hand did not find interactions between sitting, leisure time PA and risk of depression. Furthermore, in the current study, the only demographic variable showing to have an influence on the sitting– mental health relationship, but just for somatization, was age. Associations between interactions of sitting with other factors and mental health are rather mixed, so more studies should investigate this aspect to understand these complex associations. These investigations ideally would include separate measurements for specific job- and leisure-related sitting. The present data do not provide opportunities to explain the associations between sitting and mental health, however some potential mechanisms are highlighted here. Certain evidence suggests a reduced blood flow and cerebral levels of oxygen, serotonin, and endorphins during sitting.40–43 Others believe in the “displacement hypothesis,”14,44,45 which posited that sitting (eg, TV and PC time) would displace more active pursuits such as PA, that was shown to be mental health beneficial.16 However, this theory is possibly only relevant for a part of the general population. Another explanation is the “social withdrawal hypothesis,” suggesting that a lack of social interaction during sitting activities might result in poorer mental health;17,38 however, the results of Shaw and Gant39 (chat sessions decreased loneliness and depression) make believe that this might depend on the context of sitting. More research is consequently needed to detect underlying mechanisms or possible mediators of the sitting- mental health associations. Definite strengths of the current study are the large populationbased sample, which has a similar gender and age distribution compared with the Belgian population, but is higher educated than the total population. The latter may compromise generalizability of results. Furthermore, the analyses looking at interactions between sitting and demographics and PA, the inclusion of 5 distinct common mental health dimensions, and the use of separate questions to measure sitting and PA are strengths. Through these aspects, the current study adds definite new elements to the emerging literature on the relationship between sitting and (mental) health. Some limitations should also be noted. The main limitation is that the cross-sectional design does not allow establishing the direction of causality in the associations. Hence, the possibility that reduced mental health may result in higher levels of sitting cannot be ignored. Another limitation is the self-report nature of the data, possibly resulting in underestimations of sitting and overestimations of PA.46 This might explain the rather low average daily sitting time and high MVPA of this sample compared with other Belgian adults. 47,48 More objective measurement methods, such as accelerometers including an inclinometer, seem more desirable to assess sitting, but preferably in combination with a log book to assess the context of the behavior. The lack of this information (only total sitting was measured) is a third limitation. Future research might investigate the relationship between various domains of sitting (eg, occupational computer use, TV viewing, leisure time internet use) and mental health. Finally, it should be noted that effect sizes were rather small, limiting the clinical significance of findings. Effect sizes might be higher when more objective measures were used, giving more valid and reliable assessments.
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Conclusion The contribution of this study lays in examining the independent association of sedentary time with several mental health dimensions and including moderating effects of demographics and PA. The findings in the current study confirm that sedentary time is independently associated with poorer mental health outcomes. All associations were found in both men and women, and low and high educated people, some only in older individuals (> 43 years) and in those reporting less than 30 minutes of MVPA per day. Present results may specifically inform public health interventions and policy development aimed at mental health, as at risk populations are being identified.
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Acknowledgments This study was supported by Ghent University and the Belgian Scientific Institute of Public Health. The authors would like to acknowledge all subjects participating in the study. De Cocker was supported by the Research Foundation Flanders (FWO) (post-doctoral research fellowship: FWO11/ PDO/097).
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England’s health care services. Psychol Assess. 1999;11(2):159–165. doi:10.1037/1040-3590.11.2.159. 31. Jackson C. The General Health Questionnaire, 2007. Occup Med. 2007;57:79. doi:10.1093/occmed/kql169. 32. Goldberg D, Williams P. A user’s guide to the general health questionnaire. Windsor: Nfer Nelson; 1988. 33. Arrindell W, Ettema H. Symptom Checklist: Handleiding bij een multidimensionale psychopathologie indicator. Lisse: Swets & Zeitlinger; 1986. 34. Derogatis L. SCL: administration, scoring and procedures. Manual II. Baltimore: John Hopkins University School of Medicine, Clinical Psychometrics Research Unit; 1977. 35. Derogatis L, Cleary P. Confirmation of the dimensional structure of the SCL90: a study in construct validation. J Clin Psychiatry. 1977;33:981–989. 36. Yancey A, Wold C, McCarthy W, et al. Physical inactivity and overweight among Los Angeles county adults. Am J Prev Med. 2004;27:146–152. PubMed doi:10.1016/j.amepre.2004.03.012 37. Sanchez A, Norman G, Sallis JF, Calfas KJ, Rock C, Patrick K. Patterns and correlates of multiple risk behaviors in overweight women. Prev Med. 2008;46:196–202. PubMed doi:10.1016/j.ypmed.2007.10.005 38. Kraut R, Patterson M, Lundmark V, Kiesler S, Mukopadhyay T, Scherlis W. Internet paradox. A social technology that reduces social involvement and psychological well-being? Am Psychol. 1998;53:1017–1031. PubMed doi:10.1037/0003-066X.53.9.1017 39. Shaw L, Gant L. Users divided? Exploring the gender gap in internet use. Cyberpsychol Behav. 2002;5:517–527. PubMed doi:10.1089/109493102321018150 40. Levine JA, Lanningham-Foster LM, McCrady SK, Krizan AC, Olson LR, Kane PH, Jensen MD, Clark MM. Interindividual
variation in posture allocation: possible role in human obesity. Science. 2005;28;307(5709):584–6. doi:10.1126/science.1106561 41. Levine J, Yeager S. Move a little, lose a lot. US: Crown Archetype; 2009. 42. Reiff C, Marlatt K, Dengel DR. Difference in caloric expenditure in sitting versus standing desks. J Phys Act Health. 2012;9(7):1009–1011. PubMed 43. Newton RL Jr, Han H, Zderic T, Hamilton MT. The energy expenditure of sedentary behavior: a whole room calorimeter study. PLoS One. 2013;8(5):e63171. 44. Zschucke E, Gaudlitz K, Ströhle A. Exercise and physical activity in mental disorders: clinical and experimental evidence. J Prev Med Pub Health. 2013;46(Suppl 1):S12–S21 doi:10.3961/jpmph.2013.46.S.S12. PubMed 45. Dunn AL, Jewell JS. The effect of exercise on mental health. Curr Sports Med Rep. 2010;9(4):202–207 doi:10.1249/JSR.0b013e3181e7d9af. PubMed 46. Van Dyck D, Cardon G, Deforche B, De Bourdeaudhuij I. IPAQ interview version: convergent validity with accelerometers and comparison of physical activity and sedentary time levels with the self-administered version. J Sports Med Phys Fitness. 2015;55(7-8):776–86. PubMed 47. De Cocker K, De Bourdeaudhuij I, Brown W, Cardon G. The effect of a pedometer-based physical activity intervention on sitting time. Prev Med. 2008;47:179–181. PubMed doi:10.1016/j.ypmed.2008. 05.012 48. Van Dyck D, Cerin E, Conway T, et al. Associations between perceived neighbourhood environmental attributes and adults’ sedentary behavior: findings for the U.S.A., Australia and Belgium. Soc Sci Med. 2012;74:1375–1384. PubMed doi:10.1016/j.socscimed.2012. 01.018
JPAH Vol. 12, No. 8, 2015
ORIGINAL RESEARCH
Cross-Sectional Associations Between Sitting Time and Several Aspects of Mental Health in Belgian Adults Melinda Asztalos, Greet Cardon, Ilse De Bourdeaudhuij, and Katrien De Cocker Background: Sedentary behavior (including sitting) is negatively associated with physical health, independent from physical activity (PA). Knowledge on the associations with mental health is less elaborated. Therefore this study aims to investigate the relationship between sitting and 5 indices of mental health in adults (psychological distress, depression, anxiety, somatization, and sleeping problems), and between sitting interactions (sitting×gender, sitting×age, sitting×education, and sitting×PA) and these mental health indices. Methods: A cohort of Belgian adults (25–64 years; n = 4344) provided self-reported data on sitting and PA and on 5 mental health indices. Cross-sectional associations were examined using multiple linear regression analyses. Results: Analyses adjusted for gender, age, education, and PA showed significant positive associations between sitting and the 5 mental health indices (P < .05). All associations were true for both men and women, and for low and high educated individuals, while some were only found in older individuals (somatization, P < .001) and those being insufficiently active (psychological distress, P = .007; depression, P = .002; and anxiety, P = .014). Conclusions: More sitting seems to be associated with poorer mental health, independently of gender, age, education, and PA. Moderation analyses showed that these associations may differ according to age and PA levels. Keywords: sedentary behavior, survey, cross-sectional study, regression analysis
There is a solid base of scientific evidence supporting the major impact of physical activity (PA) on human physical1–3 and mental health.4–6 Recently, attention toward the independent health risks of sedentary behaviors (waking activities characterized by energy expenditure ≤ 1.5 MET in sitting or reclining posture)7 started to grow. A significant body of work in this area has been published, emphasizing that sedentary behavior is a distinctive form of human behavior that should not be considered the endpoint of the PA continuum.8 Accordingly, among the individuals who fulfill PA recommendations many may actually be just as sedentary as their inactive counterparts, and therefore, it is important to identify the health risks of actual sedentary time.9,10 The currently growing knowledge-base on the independent health outcomes of sedentary behavior shows strong associations with risks for all-cause-mortality and cardio-vascular mortality risks,11 as well as for various other chronic diseases such as diabetes, cancer, obesity, hypertension, and bone/joint-disease.10,12 Knowledge on the potential outcomes of sedentary behavior on mental health is less extensive, but starting to grow, with evidence suggesting a negative association between sedentary behavior and mental health.13–17 As mental health disorders are commonly occurring,18,19 more research on this topic is needed. In most of the previous studies only depression13,16,17 or a general mental health score14,15 were used as outcomes, while other mental health problems, such as anxiety and psychological distress are also common in the general population.20 For example, in Belgium 6% of the adult population suffers from anxiety, 8% from depression, 8% from somatization, 20% from sleeping problems, and 24% from psychological distress.21
As a result, research is needed on the association between sedentary time and a diversity of mental health indices. In addition, the influence of demographic variables, such as age, gender, and education, should be included as these were found to be related to mental health in general22,23 or were important in the PA–mental health relationship.5,6 For example, sports participation was related to less psychological distress in unemployed midaged adults, and to less perceived stress in unemployed women, unemployed young adults, and young adults with blue-collar jobs. Moreover, as previous research also showed that PA is related to mental health, and as the association between moderate-to-vigorous intensity PA (MVPA) and sedentary behavior may be high for some people but low for others, it is important to also include PA when studying the relationship between sedentary behavior and mental health. Consequently, the first aim of the current study was to analyze the relationship between sedentary time (defined here as sitting time) and 5 different mental health indices in adults, independent of gender, age, education, and PA. The hypothesis is that sitting time will be independently positively associated with psychological distress, depression, anxiety, somatization and sleeping problems. The second aim of the study was to test the associations of sitting time interaction terms (with age, gender, education and MVPA) with the mental health indices. It is hypothesized that the associations between sitting time and the mental health indices will differ according to the demographic (similar to some PA-mental health association) and PA variables.
Methods Study Design
The authors are with the Dept of Movement and Sports Sciences, Ghent University, Gent, Belgium. De Cocker ([email protected]) is corresponding author. 1112
The Belgian Health Interview Survey (B-HIS) aims at giving a description of the health status of the population by identifying health problems, describing health needs, analyzing social trends in the health status, and estimating the prevalence and distribution
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Sitting and Mental Health 1113
of health indicators.24 For the B-HIS, a multistage sampling design was applied involving a geographical stratification, a selection of clusters, a selection of household within each cluster and a selection of respondents within each household. Copies of the National Population Registry were used as the sampling frame. Invitation letters attached to informative leaflets were sent to the households of the selected individuals. Afterward, trained interviewers contacted the households’ members and explained them the objectives of the survey, obtaining their informed consent for cooperation. Data were collected through a face-to-face interview at the respondents’ home. Additional details about this multistage sampling procedure are available in the B-HIS report.24,25 With a response rate of 61.4% at household level (ie, 5530 households), the B-HIS included a total of 12,111 participants (51.1% women and 48.9% men), covering all ages from infants to 99-year-old individuals (0–24 years: n = 3254; 25–64 years: n = 6720; 65–99 years: n = 2137). The B-HIS sample has a similar gender and age distribution as the Belgian population,26 but was higher educated than the Belgian population.27 Reasons for refusing participation per household were: lack of time (22.1%), lack of interest (38.3%), old age and/or disease (6.7%), and other/unspecified reasons (32.7%) (see Figure 1). The protocol of the B-HIS was approved by the Ethical Committee of the Belgian Scientific Institute of Public Health.
Participants From the original total sample, 4344 adults (64.6% of all 25- to 64-year-olds) provided data on both sitting and mental health and
were consequently included in this study. The group of nonrespondents had the same age as the study sample, but included more men (52.6%, P < .001) and more lower educated (no diploma, primary, and lower secondary education) individuals (33.0%, P < .001) than the study sample included here.
Measurements The instruments used in this study were part of the face-to-face form of the B-HIS, which was constructed following strict protocols,24,25 and provided demographic information as well. The demographics included gender, age, and education (no diploma, primary, lower secondary, higher secondary, and higher education). International Physical Activity Questionnaire (IPAQ). The IPAQ is a valid measure for monitoring population levels of PA and sitting among 18- to 65-year-old adults in diverse settings, capturing all facets of PA (eg, transportation, occupation, household, and leisure), and sitting (eg, reading, television viewing and sitting at a desk). The IPAQ produced repeatable data (Spearman’s rho clustered around 0.8), with a criterion validity median ρ of about 0.30.28 The short, last week version of the IPAQ, particularly suitable for use in largescale surveys, was used in this study. Four questions in the IPAQ asked participants to report separately hours and minutes spent sitting on a weekday and on a weekend day during the last week. Based on participants’ reports, weekly total minutes of sitting were computed: [(weekday hours × 60) + weekday minutes] × 5 + [(weekend day hours × 60) + weekend day minutes] × 2.
Figure 1 — Flowchart B-HIS study. JPAH Vol. 12, No. 8, 2015
1114 Asztalos et al
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The IPAQ supplied also information about PA during the last week. Participants reported the following for moderate-intensity PA and vigorous-intensity PA: number of days of the last week engaged in this PA, hours engaged in this PA during 1 of those days, and minutes engaged in this PA during 1 of those days. Total minutes spent in moderate-to-vigorous intensity PA (MVPA) were computed, according to established methods posted on the IPAQ website (https://docs.google.com/viewer?a=v&pid=sites&srcid= ZGVmYXVsdGRvbWFpbnx0aGVpcGFxfGd4OjE0NDgxMDk3 NDU1YWRlZTM). General Health Questionnaire (GHQ). The first mental health index, psychological distress, which referred to overall psychological discomfort, was assessed using official translations of the GHQ.29 The GHQ is a well-established psychological screening instrument, assessing participants’ current state, and asking whether it differs from their usual state.30,31 It focuses on the inability to carry out normal functions, and the appearance of new and distressing psychological phenomena. The 12-item GHQ, used in the current study, asked about participants’ recent experiences, feelings, and thoughts (eg, Have you recently been able to concentrate on whatever you were doing?). Answer categories were on a 4-point response scale (not at all / same as usual / more than usual / much more than usual), and the bimodal scoring method was applied (ie, 0 = not at all or same as usual, 1 = more than usual or much more than usual), as this is the original scoring method.32 GHQ12 total scores were obtained by summing across all items, after reversing responses to the 6 positively stated items. Total scores ranged from 0 to 12, with higher scores indicating more psychological distress. A score of minimum 4 is known to indicate high levels of psychological distress. Cronbach’s alpha for the 12 items was 0.89 in the present sample. Symptom Check List (SCL). The other 4 mental health dimensions are feelings of depression or anxiety, symptoms of somatization, and sleeping problems, all deriving from an official translation of the SCL.33 The SCL is a widely used, valid, and reliable selfreport symptom inventory that provides an overview of a person’s symptoms and their intensity at a specific point in time (ie, last week including the day of the interview).34,35 The following 42 items (of the 90 items in the total SCL) were used in the current study: 17 items for depression (Cronbach’s α = .94) (eg, Did you cry easily in the last week, today included?), 10 items for anxiety (Cronbach’s α = .91) (eg, Did you feel nervous or shaking inside in the last week, today included?), 12 items for somatization (Cronbach’s α = .88) (eg, Did you experience chest pain in the last week, today included?), and 3 items for sleeping problems (Cronbach’s α = .80) (eg, Did you have difficulties falling asleep in the last week, today included?). Answer categories were on a 5-point Likert scale, ranging from 0 = not at all to 4 = extremely (ie, 1 = a little bit, 2 = moderately, 3 = quite a bit). Scores of 0 to 1 represent a low score of the mental health outcome and 2-3-4 stand for a high score.
health indices and of sitting with the covariates. Before conducting the multiple regressions, bivariate correlation coefficients between the independent variables were calculated to test for multicollinearity. Secondly, multiple linear regression analyses were used including sitting interaction terms (sitting×gender, sitting×age, sitting×education, and sitting×MVPA) (moderated multiple regressions) to test the statistical significance of these terms in their association with mental health dimensions. Again, 2 models were developed: one adjusted for gender, age, education, and sitting (model used for sitting×gender, sitting×age, sitting×education), and one additionally adjusted for MVPA (model used for all interactions). In case the interaction term showed to be a significant predictor, the association between sitting and mental health dimensions was assessed in 2 groups (based on the median value of the moderator) via stratified analysis. All analyses were done with SPSS 19 for Windows and standardized regression coefficients were reported. For all analyses, statistical significance was set at 0.05.
Results Table 1 presents the demographics, mental health, sitting time and MVPA scores of the individuals in the study sample. Mean age of the sample was 43.55 (SD = 11.05) years and respondents sat on average for 4.71 (SD = 2.30) hours/day. The majority was higher educated and had low scores for the mental health indices. Sitting time and the covariates were significantly associated with the mental health indices and sitting time was associated with the covariates (P < .05, data not shown). Coefficients between the Table 1 Participants Characteristics Demographics Gender: men, n (%) Age Mean (SD) years
43.55 (11.05)
Young adults (24–43 years): n (%)
2269/4344 (52.2)
Education: n (%) No diploma
58/4255 (1.4)
Primary education
391/4255 (9.2)
Lower secondary education
767/4255 (18.0)
Higher secondary education
1373/4255 (32.3)
Higher education
1666/4255 (39.2)
Mental health: mean (SD); % high score
Statistical Analyses For the first aim, multiple linear regression analyses were conducted to examine the association between sitting (predictor variable) and 5 mental health dimensions (dependent variables). Two different models were developed: 1) adjusted for demographics (gender, age, education) and 2) adjusted for demographics and MVPA. First bivariate linear regressions were conducted to test the associations of sitting and the covariates with the mental
2075/4344 (47.8)
Psychological distressa
1.30 (2.37); 13.4
Depressionb
1.30 (0.48); 1.8
Anxietyb
1.27 (0.47); 1.8
Somatizationb
1.34 (0.44); 1.2
Sleeping problemsb
1.64 (0.83); 9.9
Sitting: mean (SD) hours/day
4.71 (2.30)
MVPA: mean (SD) minutes/day
56.80 (84.41)
Score between 0–12; score ≥ 4 is considered a high score. Score between 0–4; score ≥ 2 is considered a high score. Abbreviations: MVPA, moderate-to-vigorous intensity physical activity. a
b
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Sitting and Mental Health 1115
independent variables were no higher than 0.60 (data not shown), so multicollinearity was not a problem in this study. Table 2 (see aim 1) gives an overview of the associations (beta and P-values of the controlled multiple regressions) between sitting and 5 mental health dimensions. In both models, sitting is positively associated (P < .05) with psychological distress, depression, anxiety, somatization and sleeping problems. The second aim was to look at the associations of sitting interactions (sitting×gender, sitting×age, sitting×education and sitting×MVPA) and the mental health dimensions (see Table 2, aim 2). For the sitting×gender interactions, no significant associations were found with the mental health dimensions. For age, a significant association was found between the sitting interaction
term (sitting×age) and somatization in the 2 adjusted models. Post hoc analyses stratified by age (split at median age) revealed that the association between sitting and somatization is not significant for young adults (< 43 years), while it is positive for older adults (> 43 years) (β = 0.084, P < .001). The associations between sitting*age and the other mental health dimensions were not significant. The interactions of sitting with education showed no significant associations with mental health. The interaction sitting×MVPA was significantly associated with psychological distress, depression and anxiety. Post hoc analyses stratified by MVPA showed that the associations between sitting and the 3 mental health dimensions were not significant for those reporting more than 30 minutes of MVPA daily, while for those
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Table 2 Associations Between Sitting and Mental Health and Between Sitting Interactions and Mental Health Model 1a Independent
Dependent
Model 2b
𝛃c
P
𝛃c
P 0.002
Aim 1 Sitting (ST)
Psychological distress
0.050
0.001
0.051
Depression
0.049
0.002
0.047
0.004
Anxiety
0.037
0.018
0.033
0.038
Somatization
0.045
0.004
0.042
0.008
Sleeping problems
0.043
0.006
0.044
0.006
Psychological distress
0.035
0.382
0.040
0.319
Aim 2 ST×gender
ST×age
ST×education
ST×MVPA
Depression
0.064
0.104
0.068
0.088
Anxiety
0.008
0.849
0.014
0.733
Somatization
0.015
0.701
0.014
0.731
Sleeping problems
0.014
0.722
0.019
0.631
Psychological distress
–0.005
0.950
–0.021
0.788
Depression
0.000
0.996
–0.012
0.873
Anxiety
0.026
0.727
0.015
0.841
Somatization
0.218
0.003
0.213
0.005
Sleeping problems
0.080
0.291
0.081
0.293
Psychological distress
0.003
0.946
0.002
0.976
Depression
0.019
0.705
0.012
0.821
Anxiety
0.038
0.451
0.035
0.488
Somatization
0.043
0.387
0.033
0.517
Sleeping problems
0.062
0.226
0.068
0.198
Psychological distress
–0.081
0.019
Depression
–0.098
0.004
Anxiety
–0.071
0.038
Somatization
–0.014
0.668
Sleeping problems
–0.043
0.211
Abbreviations: ST, sitting; MVPA, moderate-to-vigorous intensity physical activity. a Adjusted for gender, age and education. b Aim 1 adjusted for gender, age, education, and MVPA; aim 2 adjusted for gender, age, education, MVPA, and sitting. c Standardized coefficients. Note. Bold surfaces indicate statistically significant associations (P < .05). JPAH Vol. 12, No. 8, 2015
1116 Asztalos et al
reporting less than 30 minutes of MVPA per day, sitting was positively associated with psychological distress (β = 0.065, P = .007), depression (β = 0.074, P = .002) and anxiety (β = 0.059, P = .014). No significant associations were found between the interaction sitting×MVPA and somatization or sleeping problems.
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Discussion Because sedentary behavior research is at a stage requiring more in-depth investigations of potential mental health outcomes, the current study examined the relationship between sitting and 5 mental health dimensions in a national cohort of 4344 Belgian adults, aged 24 to 65 years. Variations across gender, age, education, and participation in MVPA in these associations were also investigated which is fairly new to the literature. The results provided evidence of the independent, positive association between sitting and the 5 mental health dimensions that were investigated (psychological distress, depression, anxiety, somatization, and sleeping problems), as analyses were controlled for demographics and MVPA. The first hypothesis (more sitting time is independently associated with poorer mental health) is hereby confirmed. Subsequent moderation analyses, testing the significance of the sitting interaction terms, found that these associations were present in both gender and both education groups. However, some of the associations of sitting with the mental health outcomes differed between both age groups and between both PA groups. The positive association between sitting and somatization was nonexistent among younger individuals and sitting was not associated with psychological distress, depression, and anxiety among those participating in MVPA. More research is needed to find out if and which other factors associated with age or PA are responsible for these findings. No other studies were found examining the association between overall sitting and several mental health dimensions, as was done in this study. However, 2 studies looking at domain-specific sitting also found associations with overall mental health. A Dutch study showed that sitting during leisure time and particularly TV viewing was associated with poorer mental health in the working population.14 Sitting during transport and sitting at work on the other hand were not associated with mental health in this crosssectional population based study of 20- to 59-year-old adults.14 In a prospective study in Spanish university graduates, those with the highest level of TV viewing and computer use showed an increased risk (31%) of developing mental health problems compared with those reporting less time in these sedentary activities.15 Furthermore, several studies looked at the association between overall sitting36,37 or domain-specific sitting,13,16,38,39 and 1 particular mental health dimension, namely depressive symptoms (while the current study looked at 5 mental health dimensions). Cross-sectional studies showed that depression was positively associated with overall sitting in Los Angeles adults36 and in 18- to 55-year-old overweight and obese women in San Diego;37 with Internet use in American households;38 with computer use, screen time, and overall sitting in 18- to 45-year-old women from Australian disadvantaged neighborhoods;13 and with leisure time computer use in 18- to 65-year-old Dutch adults.17 One longitudinal study examining the association between media use in adolescence and depression in young adulthood, revealed that more TV use had significantly greater odds of developing depression.16 The positive association between overall sitting time and depression found in the current study is in line with these previous results. Only some studies looked at joint associations between sitting and demographics or PA on mental health. In the study of Proper
and colleagues,14 working status and weight status showed to be modifiers in the associations between sitting and mental health. The findings of Sanchez-Villegas et al15 suggest that among those with lower PA levels, TV and computer use might have an import role in the incidence of anxiety, while for those with higher PA levels, these behaviors seem not to be so important. Our results show the same for anxiety, and also for psychological distress and depression. Teychenne et al13 on the other hand did not find interactions between sitting, leisure time PA and risk of depression. Furthermore, in the current study, the only demographic variable showing to have an influence on the sitting– mental health relationship, but just for somatization, was age. Associations between interactions of sitting with other factors and mental health are rather mixed, so more studies should investigate this aspect to understand these complex associations. These investigations ideally would include separate measurements for specific job- and leisure-related sitting. The present data do not provide opportunities to explain the associations between sitting and mental health, however some potential mechanisms are highlighted here. Certain evidence suggests a reduced blood flow and cerebral levels of oxygen, serotonin, and endorphins during sitting.40–43 Others believe in the “displacement hypothesis,”14,44,45 which posited that sitting (eg, TV and PC time) would displace more active pursuits such as PA, that was shown to be mental health beneficial.16 However, this theory is possibly only relevant for a part of the general population. Another explanation is the “social withdrawal hypothesis,” suggesting that a lack of social interaction during sitting activities might result in poorer mental health;17,38 however, the results of Shaw and Gant39 (chat sessions decreased loneliness and depression) make believe that this might depend on the context of sitting. More research is consequently needed to detect underlying mechanisms or possible mediators of the sitting- mental health associations. Definite strengths of the current study are the large populationbased sample, which has a similar gender and age distribution compared with the Belgian population, but is higher educated than the total population. The latter may compromise generalizability of results. Furthermore, the analyses looking at interactions between sitting and demographics and PA, the inclusion of 5 distinct common mental health dimensions, and the use of separate questions to measure sitting and PA are strengths. Through these aspects, the current study adds definite new elements to the emerging literature on the relationship between sitting and (mental) health. Some limitations should also be noted. The main limitation is that the cross-sectional design does not allow establishing the direction of causality in the associations. Hence, the possibility that reduced mental health may result in higher levels of sitting cannot be ignored. Another limitation is the self-report nature of the data, possibly resulting in underestimations of sitting and overestimations of PA.46 This might explain the rather low average daily sitting time and high MVPA of this sample compared with other Belgian adults. 47,48 More objective measurement methods, such as accelerometers including an inclinometer, seem more desirable to assess sitting, but preferably in combination with a log book to assess the context of the behavior. The lack of this information (only total sitting was measured) is a third limitation. Future research might investigate the relationship between various domains of sitting (eg, occupational computer use, TV viewing, leisure time internet use) and mental health. Finally, it should be noted that effect sizes were rather small, limiting the clinical significance of findings. Effect sizes might be higher when more objective measures were used, giving more valid and reliable assessments.
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Conclusion The contribution of this study lays in examining the independent association of sedentary time with several mental health dimensions and including moderating effects of demographics and PA. The findings in the current study confirm that sedentary time is independently associated with poorer mental health outcomes. All associations were found in both men and women, and low and high educated people, some only in older individuals (> 43 years) and in those reporting less than 30 minutes of MVPA per day. Present results may specifically inform public health interventions and policy development aimed at mental health, as at risk populations are being identified.
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Acknowledgments This study was supported by Ghent University and the Belgian Scientific Institute of Public Health. The authors would like to acknowledge all subjects participating in the study. De Cocker was supported by the Research Foundation Flanders (FWO) (post-doctoral research fellowship: FWO11/ PDO/097).
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