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Sedentary behaviour is associated with depression symptoms: Compositional data analysis from a representative sample of 3233 US adults and older adults assessed with accelerometers
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Sedentary behaviour is associated with depression symptoms: compositional data analysis from a representative sample of 3,233 US adults and older adults assessed with accelerometers Borja del Pozo Cruz , Rosa M. Alfonso-Rosa , Duncan McGregor , Prof. Sebastien F. Chastin , Javier Palarea-Albaladejo , Jesus del Pozo-Cruz PII: DOI: Reference:
S0165-0327(19)30875-4 https://doi.org/10.1016/j.jad.2020.01.023 JAD 11472
To appear in:
Journal of Affective Disorders
Received date: Revised date: Accepted date:
4 April 2019 11 November 2019 5 January 2020
Please cite this article as: Borja del Pozo Cruz , Rosa M. Alfonso-Rosa , Duncan McGregor , Prof. Sebastien F. Chastin , Javier Palarea-Albaladejo , Jesus del Pozo-Cruz , Sedentary behaviour is associated with depression symptoms: compositional data analysis from a representative sample of 3,233 US adults and older adults assessed with accelerometers, Journal of Affective Disorders (2020), doi: https://doi.org/10.1016/j.jad.2020.01.023
This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2020 Published by Elsevier B.V.
Highlights:
Evidence supporting the individual associations of sedentary behaviours with depression symptoms commonly ignores the inherent co-dependency between physical activity, sedentary behaviours and sleep in a given 24-hour period. A synergistic compositional analysis of accelerometer data uncovered a detrimental association between sedentary behaviour and depression symptoms. The observed association seems to be principally driven by corresponding reductions in moderate-to-vigorous physical activity and sleep duration. Our findings also demonstrate that reallocation of 60 minutes of sedentary behaviour to moderate-to-vigorous physical activity or sleep resulted in reduction of depression symptoms. Holistic interventions targeting sedentary time, physical activity and appropriate sleep are required to improve depression symptoms in the general population.
Sedentary behaviour is associated with depression symptoms: compositional data analysis from a representative sample of 3,233 US adults and older adults assessed with accelerometers Running head: Sitting time and depression symptoms Borja del Pozo Cruz, PhD1; Rosa M. Alfonso-Rosa, PhD2; Duncan McGregor, PhD3,4; Prof. Sebastien F. Chastin, PhD3,5; Javier Palarea-Albaladejo, PhD4; and Jesus del Pozo-Cruz, PhD2
1. Motivation and Behaviour Program, Institute for Positive Psychology and Education, Faculty of Health Sciences, Australian Catholic University, Sydney, Australia 2. Department of Physical Education and Sports, Faculty of Education, University of Seville, Seville, Spain 3. School of Health and Life Science, Glasgow Caledonian University, Glasgow, Scotland, UK 4. Biomathematics and Statistics Scotland, Edinburgh, Scotland, UK 5. Department of Movement and Sport Science, Ghent University, Ghent, Belgium
Corresponding author: Dr. Borja del Pozo Cruz Senior Research Fellow Motivation and Behaviour Research Program Institute for Positive Psychology and Education Faculty of Health Sciences Australian Catholic University Street: Level 10, 33 Berry Street, North Sydney NSW 2060 Postal: PO Box 968, North Sydney NSW 2059 Office: +61 2 9701 4644 Mobile: +61 451083464 Email: [email protected] Web: http://www.acu.edu.au/ippe/
Abstract Background: Evidence supporting the individual associations of sedentary behaviours with depression symptoms commonly ignores the inherent co-dependency between physical activity, sedentary behaviours and sleep in a given 24-hour period. Data analysis based on compositional methods effectively deals with this issue. Aim: To investigate the association between sedentary behaviour and depression symptoms synergistically using compositional analysis methods. Methods: Participants were a representative sample of 3,233 US adults and older adults from the 2005-2006 cycle of the NHANES with valid 24-hour lifestyle behaviours data (i.e., accelerometer-derived physical activity and sedentary behaviour and self-reported sleep) and available self-reported depression symptoms (PHQ-9). The association between sedentary
behaviour and depression symptoms scoring was investigated using a compositional zeroinflated Poisson regression analysis. Subsequently, the model estimates were used to evaluate the effects on depression symptoms of replacing time spent in sitting activities with physical activity of different intensities and sleep. Limitations: The current study is limited by its cross-sectional design. Also, sleep time was self-reported, which could bias our estimations. Results: Increased sedentary behaviour relative to other behaviours was statistically significantly associated with increased depression symptoms (p < 0.001). Reallocating 60 minutes time from sedentary behaviours to moderate-to-vigorous physical activity (MVPA) and sleep was associated with small reductions in depression symptoms. Conclusions: A synergistic compositional analysis of accelerometer data uncovered a detrimental association between sedentary behaviour and depression symptoms. These results add to evidence from previous studies. The observed association seems to be principally driven by corresponding reductions in MVPA and sleep duration. Key words: Sitting time; time use; depression disorders; compositional data analysis
Introduction Sedentary behaviour has emerged as a modifiable factor with negative health consequences, including obesity (Golubic et al., 2015) and all-cause mortality (Biswas et al., 2015). More recent evidence has also linked time spent in sedentary activities with depression symptoms. A recent meta-analysis (Zhai, Zhang, & Zhang, 2015b) reported that sedentary behaviour was significantly associated with an increased risk of depression. Lifestyle behaviours are compositional in nature: people have a fixed amount of time in a given day (i.e., 24 hours), and time spent in one domain (e.g. sedentary behaviour) is inherently intertwined with time spent in others (e.g. sleep or physical activity) via substitution effects and latent lifestyle choices. Unlike standard procedures, the compositional approach effectively considers this in a well-principled manner (Pawlowsky-Glahn, Egozcue, & Tolosana-Delgado, 2015). Compositional data analysis through log-ratio coordinates allows inferences to be made from constrained data carrying relative information, such as physical activity data. Application of compositional data methods has led to new evidence on the impact of the 24-hour lifestyle behaviours on a wide range of health outcomes (Carson, Tremblay, Chaput, & Chastin, 2016; McGregor et al., 2018). It is plausible that the impact of sedentary behaviour on depends on the rest of the time is spent throughout the day, which might explain, at least in part, some of the inconsistencies observed in previous studies (Zhai et al., 2015b). Recently, Abe et al. (Abe et al., 2019) suggested a combined effect of physical activity and sitting on depressive symptoms in rural
Japanese adults. To our knowledge, there are no existing studies that explicitly evaluate the impact of sedentary behaviours on depression symptoms while accounting for physical activity and sleep. The aim of this study was to examine the relationship between sedentary behaviour and depression symptoms using a compositional approach to fully account for the time spent in physical activity and sleep and their interplay. Methods Study design and participants This study is a secondary data analysis of the 2005-2006 cycle of the National Health and Nutrition Examination Survey (NHANES). Description of the method and procedures used are detailed elsewhere (Zipf et al., 2013). Briefly, the NHANES comprises a series of crosssectional surveys every two years designed to gather information around the health and nutrition, including physical activity, sedentary behaviour, sleep, and mental health in a representative sample of the US population. The ethics committee of the Centres approved the original study for Disease Control and Prevention and all participants gave informed consent. Participants were adults 18 years old or older participating in the NHANES cycle 2005-2006. Non-pregnant participants with 4 or more valid days of valid accelerometry data (8 hours/day) and available self-reported depression symptoms data were initially included in the study (n = 3,256). Participants with self-reported severe depression were excluded from the study (n = 23). Measures 24-hour lifestyle behaviours (exposure) Physical activity and sedentary behavior were assessed during 7 consecutive days by uniaxial accelerometry (AM-7164, ActiGraph, LLC, Pensacola, FL). Participants in the NHANES were asked to wear the accelerometer in an elastic waistband on the hip during waking hours, except while bathing or swimming activities. The resulting acceleration counts from the devices were integrated over 1-min epochs and were used to classify people's activities such as <100 counts per minute (cpm) represented sedentary behaviour, 100 to <2020 cpm represented light intensity activity (LIPA), and ≥2020 cpm represented moderate-to-vigorous activity (MVPA) (Theou, Blodgett, Godin, & Rockwood, 2017). Daily distributions of time averaged over the number of valid days to derive an estimate of the mean time (min) spent in each of the assessed intensities per day. Participants were asked to self-report duration of daily sleep (h/day, then transformed to min/day) as part of the completion of the validated Sleep Disorder Questionnaire (Violani, Devoto, Lucidi, Lombardo, & Russo, 2004). Depression symptoms (outcome) Depression symptoms were assessed using the Patient Health Questionnaire-9 (PHQ-9), a 9item self-report depression questionnaire that asks questions about the frequency of symptoms of depression over the past 2 weeks. The PHQ-9 has demonstrated excellent internal consistency (Cronbach's α of 0.89) and item responses and total scores on the PHQ-
9 follow the characteristic distributions, consistent with other depression screening scales (Tomitaka et al., 2018). Each item ranges from 0 (not at all) to 3 (nearly every day), and they are added into a total PHQ-9 score taking discrete values from 0 (no symptoms) to 27 (severe symptoms), with scores =>10 representing major depression symptoms. Covariates Participants in the NHANES cycle 2005-2006 self-reported their age, sex, ethnicity, education, marital status, income and presence of chronic diseases. Participants were categorized as current smokers if their serum cotinine concentration was 10 ng/mL or more (Duque et al., 2017). Body height and weight were objectively measured by a trained health technician as part of the examination protocol in NHANES. Body mass index was calculated as weight in kilograms divided by height in meters squared. Statistical analysis All analyses were conducted in the R system for statistical computing v 3.5.0 (R Development Core Team, Vienna, Austria) and statistical significance was set at the usual 0.05 level. Ordinary summary statistics were used to describe participants in the study on key demographic characteristics. In accordance with the relative scale of compositional data (Pawlowsky-Glahn et al., 2015) the geometric mean was used to summarize daily time (%) across all 24-hour lifestyle behaviours. Compositional analysis was conducted using methods implemented in the R packages Compositions (van den Boogaart & Tolosana-Delgado, 2008) and zCompositions (PalareaAlbaladejo & Martín-Fernández, 2015). This latter facilitated pre-processing of zero observations to be replaced by plausible small values using the log-ratio ExpectationMaximisation algorithm. Each participant ́s daily time use was considered as a composition [sedentary behaviour, LIPA, MVPA, sleep] with the (geometric) mean daily time spent in each part of the composition normalized to sum 1440 min (i.e., 100% of the available time in a given day). The application of compositional data analysis to 24-hour time-use has been described in detail elsewhere (Chastin, Palarea-Albaladejo, Dontje, & Skelton, 2015; Pawlowsky-Glahn et al., 2015). Participants’ time use compositions were expressed as three isometric log-ratio (ilr) coordinates. The first ilr-coordinate contained all the relative information of the sedentary behaviour part with respect to the geometric mean of the remaining parts in the composition (i.e. physical activity behaviours and sleep time) as described in (Chastin et al., 2015). These ilr-coordinates were used as exposure variables in a zero-inflated Poisson (ZIP) regression model fitted to the PHQ-9 depression score as a count response (outcome) variable. This model allowed to adequately account for the excess of zeros and non-normal distribution of count data, separating the depression presence/absence binomial process (positive vs. zero scores) from the Poisson count process determining the depression symptom scores, The model was adjusted for relevant covariates including age, sex, ethnicity, marital status, income, presence of chronic diseases, current smoking status and body mass index. Coefficients from the count part of the model were used in compositional isotemporal substitution analysis (Chastin et al., 2015) to estimate the expected change in depression symptoms from replacing sedentary behaviour (0 to 60 minutes) with either LIPA, MVPA, or Sleep.
Results The analytic sample comprised 3,233 participants that provided valid accelerometer data and depression symptoms. Table 1 shows the key characteristics of study participants. Mean age of participants (52.1% female; 47.9% male) was 47.43 years (77% less than 65 years old). Prevalence of current smokers was 21.6%, and 39.3% had at least 1 chronic disease. Participants in the study spent most of their time sedentary (40.47% time) and engaged in very little MVPA (1.88% time). The ZIP regression analysis estimates showed that time spent in sedentary behaviour relative to time spent in other behaviours was associated with increased depression symptoms (p<0.001, Supplementary Table 1). Using the fitted model, Fig. 1 shows the expected effect on depression symptoms of replacing 1 to 60 minutes of sedentary behaviour with MVPA, LIPA and Sleep from the overall mean composition of (sedentary behaviour, 589.05 min/day; LIPA, 304.85 min/day; MVPA, 14.57 min/day; and Sleep, 531.51 min/day). Replacing 60 minutes of sedentary behaviour with MVPA or sleep was statistically associated with a reduction of -0.09 (95%CI -0.16 to -0.02) and -0.08 (95%CI -0.10 to -0.05) on the PHQ-9 scale respectively. Replacing sedentary behaviour with LIPA did not yield a significant result (Figure 1). Discussion In the current study, we demonstrate that time spent in sedentary behaviour, while formally accounting for its interplay with time spent in physical activity and sleep duration using a compositional analysis approach, is detrimentally associated with depression symptoms in a representative sample of 3,233 US adults and older adults. The results from this study add to evidence from other previous studies (Zhai et al., 2015b). Using our modelling approach, we were able to estimate a beneficial association with depression symptoms from replacing sedentary behaviour with either moderate-to-vigorous physical activity or sleep. Ultimately, our results align with the idea that a comprehensive 24-hour lifestyle management approach may be beneficial to effectively reduce depression symptoms in the general population. The compositional isotemporal analysis performed in this study suggests that changes in depression symptoms associated with sedentary behaviour are moderated by changes in moderate-to-vigorous physical activity and sleep duration. These results support an integrated role of sedentary behaviour (Zhai et al., 2015b), moderate-to-vigorous physical activity (Mc Dowell et al., 2018) and sleep (Zhai, Zhang, & Zhang, 2015a) on depression symptoms. These findings are relevant to public health; interventions should move from targeting single behaviours (e.g., sedentary behaviours) to more integrated approaches where all 24-hour lifestyle behaviours are considered. The small effect sizes detected in this study are consistent with previous estimates (Yasunaga, Shibata, Ishii, Koohsari, & Oka, 2018). Factors such as our population being considered nonclinical population may partly explain this observation. In a previous meta-analysis, Rebar et al. (Rebar et al., 2015) suggested that the effects of physical activity on depression may be somewhat weaker for non-clinical populations compared to clinical populations. Nonetheless, the continuous exposure to physical activity can reduce depression symptoms (Rebar et al., 2015) and prevent the onset of depression among the general adult population (Schuch et al., 2018). Therefore, our findings extend those from previous reports and remain clinically
relevant: daily replacement of sedentary behaviour with MVPA and sleep may result in the prevention of onset depression symptoms in healthy individuals. The current study is limited by its cross-sectional design, which precludes us from claiming any causal inference from the results (i.e., reverse causality cannot be ruled out). Also, sleep time was self-reported which may bias our estimates. Lastly, the majority of the sample were adults (77%) so these findings may not be representative of older adults if depression has different association patterns with time-use between these two age-groups, e.g. light activities may be associated with a larger decrease in depression symptoms for older adults. A major methodological strength in this study was the application of compositional data analysis techniques, which enabled an integrated assessment of the association between sedentary behaviour and depression symptoms while accounting for the interplay with other behaviours. Another strength is the use of accelerometers for assessing sedentary behaviour and physical activity. Conclusions Sedentary time, relative to time spent in physical activity and sleep, is statistically significantly associated with depression symptoms in the study sample. The results of this study largely agree with previous evidence and suggest that moderate-to-vigorous physical activity and sleep duration moderate changes in depression symptoms associated with sedentary behaviours. Our findings support the need for more holistic interventions that target sedentary time, physical activity (particularly of moderate-to-vigorous intensity) and appropriate sleep in order to improve depression symptoms in the general population. These findings warrant further experimental research. Conflict of interest: None of the authors have any conflict of interest to declare Contributions: BdPC designed the study, wrote the initial draft and conducted formal analyses. JdPC and RAR helped conceptualizing the idea and critically reviewed the manuscript. DM, JP, and SC critically reviewed the manuscript and provided input. All authors contributed to and have approved the final manuscript. Acknowledgements: None. Role of funding source: D. McGregor and J. Palarea-Albaladejo have been supported by the Scottish Government’s Rural and Environment Science and Analytical Services Division (RESAS). J. PalareaAlbaladejo has also been supported by the Spanish Ministry of Economy and Competitiveness under the project CODA-RETOS MTM2015-65016-C2-1(2)-R
References Abe, T., Hamano, T., Onoda, K., Takeda, M., Okuyama, K., Yamasaki, M., … Nabika, T. (2019). Additive Effect of Physical Activity and Sedentary Time on Depressive Symptoms in Rural Japanese Adults: A Cross-Sectional Study. Journal of Epidemiology / Japan Epidemiological Association, 29(6), 227–232. Biswas, A., Oh, P. I., Faulkner, G. E., Bajaj, R. R., Silver, M. A., Mitchell, M. S., & Alter, D. A. (2015). Sedentary time and its association with risk for disease incidence, mortality, and hospitalization in adults: a systematic review and meta-analysis. Annals of Internal Medicine, 162(2), 123–132. Carson, V., Tremblay, M. S., Chaput, J.-P., & Chastin, S. F. M. (2016). Associations between sleep duration, sedentary time, physical activity, and health indicators among Canadian children and youth using compositional analyses. Applied Physiology, Nutrition, and Metabolism = Physiologie Appliquee, Nutrition et Metabolisme, 41(6 Suppl 3), S294– S302. Chastin, S. F. M., Palarea-Albaladejo, J., Dontje, M. L., & Skelton, D. A. (2015). Combined Effects of Time Spent in Physical Activity, Sedentary Behaviors and Sleep on Obesity and Cardio-Metabolic Health Markers: A Novel Compositional Data Analysis Approach. PloS One, 10(10), e0139984. Duque, A., Martínez, P.-J., Giraldo, A., Gualtero, D.-F., Ardila, C.-M., Contreras, A., … Lafaurie, G.-I. (2017). Accuracy of cotinine serum test to detect the smoking habit and its association with periodontal disease in a multicenter study. Medicina Oral, Patologia Oral Y Cirugia Bucal, 22(4), e425–e431. Golubic, R., Wijndaele, K., Sharp, S. J., Simmons, R. K., Griffin, S. J., Wareham, N. J., … ProActive Study Group. (2015). Physical activity, sedentary time and gain in overall and central body fat: 7-year follow-up of the ProActive trial cohort. International Journal of Obesity , 39(1), 142–148. Mc Dowell, C. P., Carlin, A., Capranica, L., Dillon, C., Harrington, J. M., Lakerveld, J., … Herring, M. P. (2018). Associations of self-reported physical activity and depression in 10,000 Irish adults across harmonised datasets: a DEDIPAC-study. BMC Public Health, 18(1), 779. McGregor, D. E., Carson, V., Palarea-Albaladejo, J., Dall, P. M., Tremblay, M. S., & Chastin, S. F. M. (2018). Compositional Analysis of the Associations between 24-h Movement Behaviours and Health Indicators among Adults and Older Adults from the Canadian Health Measure Survey. International Journal of Environmental Research and Public Health, 15(8). https://doi.org/10.3390/ijerph15081779 Palarea-Albaladejo, J., & Martín-Fernández, J. A. (2015). zCompositions — R package for multivariate imputation of left-censored data under a compositional approach. Chemometrics and Intelligent Laboratory Systems, 143, 85–96. Pawlowsky-Glahn, V., Egozcue, J. J., & Tolosana-Delgado, R. (2015). Modelling and Analysis of Compositional Data. https://doi.org/10.1002/9781119003144 Rebar, A. L., Stanton, R., Geard, D., Short, C., Duncan, M. J., & Vandelanotte, C. (2015). A meta-meta-analysis of the effect of physical activity on depression and anxiety in nonclinical adult populations. Health Psychology Review, 9(3), 366–378. Schuch, F. B., Vancampfort, D., Firth, J., Rosenbaum, S., Ward, P. B., Silva, E. S., … Stubbs, B. (2018). Physical Activity and Incident Depression: A Meta-Analysis of Prospective Cohort Studies. The American Journal of Psychiatry, 175(7), 631–648. Theou, O., Blodgett, J. M., Godin, J., & Rockwood, K. (2017). Association between sedentary time and mortality across levels of frailty. CMAJ: Canadian Medical Association Journal = Journal de l’Association Medicale Canadienne, 189(33), E1056–E1064. Tomitaka, S., Kawasaki, Y., Ide, K., Akutagawa, M., Yamada, H., Ono, Y., & Furukawa, T. A. (2018). Distributional patterns of item responses and total scores on the PHQ-9 in the general population: data from the National Health and Nutrition Examination Survey. BMC Psychiatry, 18(1), 108. van den Boogaart, K. G., & Tolosana-Delgado, R. (2008). “compositions”: A unified R package
to analyze compositional data. Computers & Geosciences, 34(4), 320–338. Violani, C., Devoto, A., Lucidi, F., Lombardo, C., & Russo, P. M. (2004). Validity of a short insomnia questionnaire: the SDQ. Brain Research Bulletin, 63(5), 415–421. Yasunaga, A., Shibata, A., Ishii, K., Koohsari, M. J., & Oka, K. (2018). Cross-sectional associations of sedentary behaviour and physical activity on depression in Japanese older adults: an isotemporal substitution approach. BMJ Open, 8(9), e022282. Zhai, L., Zhang, H., & Zhang, D. (2015a). Sleep duration and depression among adults: a meta-analysis of prospective studies. Depression and Anxiety, 32(9), 664–670. Zhai, L., Zhang, Y., & Zhang, D. (2015b). Sedentary behaviour and the risk of depression: a meta-analysis. British Journal of Sports Medicine, 49(11), 705–709. Zipf, G., Chiappa, M., Porter, K. S., Ostchega, Y., Lewis, B. G., & Dostal, J. (2013). National health and nutrition examination survey: plan and operations, 1999-2010. Vital and Health Statistics. Ser. 1, Programs and Collection Procedures, (56), 1–37.
Figure legends: Figure 1. Estimated reduction in depression symptoms (as measured by the PHQ-9 depression score scale) associated with reallocating time from sedentary behaviour to another behaviour (Light intensity physical activity, Moderate-to-vigorous physical activity, and Sleep) from the mean overall composition of (589.05, 304.85, 14.57, 531.51). The green line in the figure represents the theoretical change in depression symptom scores (PHQ-9) from replacing time spent in sedentary behaviour with time spent in Moderate-to-vigorous physical activity. For example, replacing 60 minutes of sedentary time with 60 minutes Moderate-tovigorous physical activity would result in a reduction of -0.09 points in depression symptoms.
Table 1. Descriptive characteristics of the sample (n= 3,233) Age (yr.) Gender, female, % Body Mass Index (Kg/m2) Current smokers, %
47.43 (19.45) 52.1 28.58 (6.74) 21.6
Depression symptoms (PHQ-9)
2.51 (3.38)
At least 1 chronic condition, %
39.3
Sleep (%)*
36.19
Sedentary behaviour (%)*
40.47
Light intensity physical activity (%)*
21.45
Moderate-to-vigorous physical activity (%)*
1.88
Values are arithmetic mean (SD) unless otherwise stated. *Geometric mean normalized to 100% of time. PHQ-9: Patient Health Questionnaire-9 items
Sedentary behaviour is associated with depression symptoms: compositional data analysis from a representative sample of 3,233 US adults and older adults assessed with accelerometers Borja del Pozo Cruz , Rosa M. Alfonso-Rosa , Duncan McGregor , Prof. Sebastien F. Chastin , Javier Palarea-Albaladejo , Jesus del Pozo-Cruz PII: DOI: Reference:
S0165-0327(19)30875-4 https://doi.org/10.1016/j.jad.2020.01.023 JAD 11472
To appear in:
Journal of Affective Disorders
Received date: Revised date: Accepted date:
4 April 2019 11 November 2019 5 January 2020
Please cite this article as: Borja del Pozo Cruz , Rosa M. Alfonso-Rosa , Duncan McGregor , Prof. Sebastien F. Chastin , Javier Palarea-Albaladejo , Jesus del Pozo-Cruz , Sedentary behaviour is associated with depression symptoms: compositional data analysis from a representative sample of 3,233 US adults and older adults assessed with accelerometers, Journal of Affective Disorders (2020), doi: https://doi.org/10.1016/j.jad.2020.01.023
This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2020 Published by Elsevier B.V.
Highlights:
Evidence supporting the individual associations of sedentary behaviours with depression symptoms commonly ignores the inherent co-dependency between physical activity, sedentary behaviours and sleep in a given 24-hour period. A synergistic compositional analysis of accelerometer data uncovered a detrimental association between sedentary behaviour and depression symptoms. The observed association seems to be principally driven by corresponding reductions in moderate-to-vigorous physical activity and sleep duration. Our findings also demonstrate that reallocation of 60 minutes of sedentary behaviour to moderate-to-vigorous physical activity or sleep resulted in reduction of depression symptoms. Holistic interventions targeting sedentary time, physical activity and appropriate sleep are required to improve depression symptoms in the general population.
Sedentary behaviour is associated with depression symptoms: compositional data analysis from a representative sample of 3,233 US adults and older adults assessed with accelerometers Running head: Sitting time and depression symptoms Borja del Pozo Cruz, PhD1; Rosa M. Alfonso-Rosa, PhD2; Duncan McGregor, PhD3,4; Prof. Sebastien F. Chastin, PhD3,5; Javier Palarea-Albaladejo, PhD4; and Jesus del Pozo-Cruz, PhD2
1. Motivation and Behaviour Program, Institute for Positive Psychology and Education, Faculty of Health Sciences, Australian Catholic University, Sydney, Australia 2. Department of Physical Education and Sports, Faculty of Education, University of Seville, Seville, Spain 3. School of Health and Life Science, Glasgow Caledonian University, Glasgow, Scotland, UK 4. Biomathematics and Statistics Scotland, Edinburgh, Scotland, UK 5. Department of Movement and Sport Science, Ghent University, Ghent, Belgium
Corresponding author: Dr. Borja del Pozo Cruz Senior Research Fellow Motivation and Behaviour Research Program Institute for Positive Psychology and Education Faculty of Health Sciences Australian Catholic University Street: Level 10, 33 Berry Street, North Sydney NSW 2060 Postal: PO Box 968, North Sydney NSW 2059 Office: +61 2 9701 4644 Mobile: +61 451083464 Email: [email protected] Web: http://www.acu.edu.au/ippe/
Abstract Background: Evidence supporting the individual associations of sedentary behaviours with depression symptoms commonly ignores the inherent co-dependency between physical activity, sedentary behaviours and sleep in a given 24-hour period. Data analysis based on compositional methods effectively deals with this issue. Aim: To investigate the association between sedentary behaviour and depression symptoms synergistically using compositional analysis methods. Methods: Participants were a representative sample of 3,233 US adults and older adults from the 2005-2006 cycle of the NHANES with valid 24-hour lifestyle behaviours data (i.e., accelerometer-derived physical activity and sedentary behaviour and self-reported sleep) and available self-reported depression symptoms (PHQ-9). The association between sedentary
behaviour and depression symptoms scoring was investigated using a compositional zeroinflated Poisson regression analysis. Subsequently, the model estimates were used to evaluate the effects on depression symptoms of replacing time spent in sitting activities with physical activity of different intensities and sleep. Limitations: The current study is limited by its cross-sectional design. Also, sleep time was self-reported, which could bias our estimations. Results: Increased sedentary behaviour relative to other behaviours was statistically significantly associated with increased depression symptoms (p < 0.001). Reallocating 60 minutes time from sedentary behaviours to moderate-to-vigorous physical activity (MVPA) and sleep was associated with small reductions in depression symptoms. Conclusions: A synergistic compositional analysis of accelerometer data uncovered a detrimental association between sedentary behaviour and depression symptoms. These results add to evidence from previous studies. The observed association seems to be principally driven by corresponding reductions in MVPA and sleep duration. Key words: Sitting time; time use; depression disorders; compositional data analysis
Introduction Sedentary behaviour has emerged as a modifiable factor with negative health consequences, including obesity (Golubic et al., 2015) and all-cause mortality (Biswas et al., 2015). More recent evidence has also linked time spent in sedentary activities with depression symptoms. A recent meta-analysis (Zhai, Zhang, & Zhang, 2015b) reported that sedentary behaviour was significantly associated with an increased risk of depression. Lifestyle behaviours are compositional in nature: people have a fixed amount of time in a given day (i.e., 24 hours), and time spent in one domain (e.g. sedentary behaviour) is inherently intertwined with time spent in others (e.g. sleep or physical activity) via substitution effects and latent lifestyle choices. Unlike standard procedures, the compositional approach effectively considers this in a well-principled manner (Pawlowsky-Glahn, Egozcue, & Tolosana-Delgado, 2015). Compositional data analysis through log-ratio coordinates allows inferences to be made from constrained data carrying relative information, such as physical activity data. Application of compositional data methods has led to new evidence on the impact of the 24-hour lifestyle behaviours on a wide range of health outcomes (Carson, Tremblay, Chaput, & Chastin, 2016; McGregor et al., 2018). It is plausible that the impact of sedentary behaviour on depends on the rest of the time is spent throughout the day, which might explain, at least in part, some of the inconsistencies observed in previous studies (Zhai et al., 2015b). Recently, Abe et al. (Abe et al., 2019) suggested a combined effect of physical activity and sitting on depressive symptoms in rural
Japanese adults. To our knowledge, there are no existing studies that explicitly evaluate the impact of sedentary behaviours on depression symptoms while accounting for physical activity and sleep. The aim of this study was to examine the relationship between sedentary behaviour and depression symptoms using a compositional approach to fully account for the time spent in physical activity and sleep and their interplay. Methods Study design and participants This study is a secondary data analysis of the 2005-2006 cycle of the National Health and Nutrition Examination Survey (NHANES). Description of the method and procedures used are detailed elsewhere (Zipf et al., 2013). Briefly, the NHANES comprises a series of crosssectional surveys every two years designed to gather information around the health and nutrition, including physical activity, sedentary behaviour, sleep, and mental health in a representative sample of the US population. The ethics committee of the Centres approved the original study for Disease Control and Prevention and all participants gave informed consent. Participants were adults 18 years old or older participating in the NHANES cycle 2005-2006. Non-pregnant participants with 4 or more valid days of valid accelerometry data (8 hours/day) and available self-reported depression symptoms data were initially included in the study (n = 3,256). Participants with self-reported severe depression were excluded from the study (n = 23). Measures 24-hour lifestyle behaviours (exposure) Physical activity and sedentary behavior were assessed during 7 consecutive days by uniaxial accelerometry (AM-7164, ActiGraph, LLC, Pensacola, FL). Participants in the NHANES were asked to wear the accelerometer in an elastic waistband on the hip during waking hours, except while bathing or swimming activities. The resulting acceleration counts from the devices were integrated over 1-min epochs and were used to classify people's activities such as <100 counts per minute (cpm) represented sedentary behaviour, 100 to <2020 cpm represented light intensity activity (LIPA), and ≥2020 cpm represented moderate-to-vigorous activity (MVPA) (Theou, Blodgett, Godin, & Rockwood, 2017). Daily distributions of time averaged over the number of valid days to derive an estimate of the mean time (min) spent in each of the assessed intensities per day. Participants were asked to self-report duration of daily sleep (h/day, then transformed to min/day) as part of the completion of the validated Sleep Disorder Questionnaire (Violani, Devoto, Lucidi, Lombardo, & Russo, 2004). Depression symptoms (outcome) Depression symptoms were assessed using the Patient Health Questionnaire-9 (PHQ-9), a 9item self-report depression questionnaire that asks questions about the frequency of symptoms of depression over the past 2 weeks. The PHQ-9 has demonstrated excellent internal consistency (Cronbach's α of 0.89) and item responses and total scores on the PHQ-
9 follow the characteristic distributions, consistent with other depression screening scales (Tomitaka et al., 2018). Each item ranges from 0 (not at all) to 3 (nearly every day), and they are added into a total PHQ-9 score taking discrete values from 0 (no symptoms) to 27 (severe symptoms), with scores =>10 representing major depression symptoms. Covariates Participants in the NHANES cycle 2005-2006 self-reported their age, sex, ethnicity, education, marital status, income and presence of chronic diseases. Participants were categorized as current smokers if their serum cotinine concentration was 10 ng/mL or more (Duque et al., 2017). Body height and weight were objectively measured by a trained health technician as part of the examination protocol in NHANES. Body mass index was calculated as weight in kilograms divided by height in meters squared. Statistical analysis All analyses were conducted in the R system for statistical computing v 3.5.0 (R Development Core Team, Vienna, Austria) and statistical significance was set at the usual 0.05 level. Ordinary summary statistics were used to describe participants in the study on key demographic characteristics. In accordance with the relative scale of compositional data (Pawlowsky-Glahn et al., 2015) the geometric mean was used to summarize daily time (%) across all 24-hour lifestyle behaviours. Compositional analysis was conducted using methods implemented in the R packages Compositions (van den Boogaart & Tolosana-Delgado, 2008) and zCompositions (PalareaAlbaladejo & Martín-Fernández, 2015). This latter facilitated pre-processing of zero observations to be replaced by plausible small values using the log-ratio ExpectationMaximisation algorithm. Each participant ́s daily time use was considered as a composition [sedentary behaviour, LIPA, MVPA, sleep] with the (geometric) mean daily time spent in each part of the composition normalized to sum 1440 min (i.e., 100% of the available time in a given day). The application of compositional data analysis to 24-hour time-use has been described in detail elsewhere (Chastin, Palarea-Albaladejo, Dontje, & Skelton, 2015; Pawlowsky-Glahn et al., 2015). Participants’ time use compositions were expressed as three isometric log-ratio (ilr) coordinates. The first ilr-coordinate contained all the relative information of the sedentary behaviour part with respect to the geometric mean of the remaining parts in the composition (i.e. physical activity behaviours and sleep time) as described in (Chastin et al., 2015). These ilr-coordinates were used as exposure variables in a zero-inflated Poisson (ZIP) regression model fitted to the PHQ-9 depression score as a count response (outcome) variable. This model allowed to adequately account for the excess of zeros and non-normal distribution of count data, separating the depression presence/absence binomial process (positive vs. zero scores) from the Poisson count process determining the depression symptom scores, The model was adjusted for relevant covariates including age, sex, ethnicity, marital status, income, presence of chronic diseases, current smoking status and body mass index. Coefficients from the count part of the model were used in compositional isotemporal substitution analysis (Chastin et al., 2015) to estimate the expected change in depression symptoms from replacing sedentary behaviour (0 to 60 minutes) with either LIPA, MVPA, or Sleep.
Results The analytic sample comprised 3,233 participants that provided valid accelerometer data and depression symptoms. Table 1 shows the key characteristics of study participants. Mean age of participants (52.1% female; 47.9% male) was 47.43 years (77% less than 65 years old). Prevalence of current smokers was 21.6%, and 39.3% had at least 1 chronic disease. Participants in the study spent most of their time sedentary (40.47% time) and engaged in very little MVPA (1.88% time). The ZIP regression analysis estimates showed that time spent in sedentary behaviour relative to time spent in other behaviours was associated with increased depression symptoms (p<0.001, Supplementary Table 1). Using the fitted model, Fig. 1 shows the expected effect on depression symptoms of replacing 1 to 60 minutes of sedentary behaviour with MVPA, LIPA and Sleep from the overall mean composition of (sedentary behaviour, 589.05 min/day; LIPA, 304.85 min/day; MVPA, 14.57 min/day; and Sleep, 531.51 min/day). Replacing 60 minutes of sedentary behaviour with MVPA or sleep was statistically associated with a reduction of -0.09 (95%CI -0.16 to -0.02) and -0.08 (95%CI -0.10 to -0.05) on the PHQ-9 scale respectively. Replacing sedentary behaviour with LIPA did not yield a significant result (Figure 1). Discussion In the current study, we demonstrate that time spent in sedentary behaviour, while formally accounting for its interplay with time spent in physical activity and sleep duration using a compositional analysis approach, is detrimentally associated with depression symptoms in a representative sample of 3,233 US adults and older adults. The results from this study add to evidence from other previous studies (Zhai et al., 2015b). Using our modelling approach, we were able to estimate a beneficial association with depression symptoms from replacing sedentary behaviour with either moderate-to-vigorous physical activity or sleep. Ultimately, our results align with the idea that a comprehensive 24-hour lifestyle management approach may be beneficial to effectively reduce depression symptoms in the general population. The compositional isotemporal analysis performed in this study suggests that changes in depression symptoms associated with sedentary behaviour are moderated by changes in moderate-to-vigorous physical activity and sleep duration. These results support an integrated role of sedentary behaviour (Zhai et al., 2015b), moderate-to-vigorous physical activity (Mc Dowell et al., 2018) and sleep (Zhai, Zhang, & Zhang, 2015a) on depression symptoms. These findings are relevant to public health; interventions should move from targeting single behaviours (e.g., sedentary behaviours) to more integrated approaches where all 24-hour lifestyle behaviours are considered. The small effect sizes detected in this study are consistent with previous estimates (Yasunaga, Shibata, Ishii, Koohsari, & Oka, 2018). Factors such as our population being considered nonclinical population may partly explain this observation. In a previous meta-analysis, Rebar et al. (Rebar et al., 2015) suggested that the effects of physical activity on depression may be somewhat weaker for non-clinical populations compared to clinical populations. Nonetheless, the continuous exposure to physical activity can reduce depression symptoms (Rebar et al., 2015) and prevent the onset of depression among the general adult population (Schuch et al., 2018). Therefore, our findings extend those from previous reports and remain clinically
relevant: daily replacement of sedentary behaviour with MVPA and sleep may result in the prevention of onset depression symptoms in healthy individuals. The current study is limited by its cross-sectional design, which precludes us from claiming any causal inference from the results (i.e., reverse causality cannot be ruled out). Also, sleep time was self-reported which may bias our estimates. Lastly, the majority of the sample were adults (77%) so these findings may not be representative of older adults if depression has different association patterns with time-use between these two age-groups, e.g. light activities may be associated with a larger decrease in depression symptoms for older adults. A major methodological strength in this study was the application of compositional data analysis techniques, which enabled an integrated assessment of the association between sedentary behaviour and depression symptoms while accounting for the interplay with other behaviours. Another strength is the use of accelerometers for assessing sedentary behaviour and physical activity. Conclusions Sedentary time, relative to time spent in physical activity and sleep, is statistically significantly associated with depression symptoms in the study sample. The results of this study largely agree with previous evidence and suggest that moderate-to-vigorous physical activity and sleep duration moderate changes in depression symptoms associated with sedentary behaviours. Our findings support the need for more holistic interventions that target sedentary time, physical activity (particularly of moderate-to-vigorous intensity) and appropriate sleep in order to improve depression symptoms in the general population. These findings warrant further experimental research. Conflict of interest: None of the authors have any conflict of interest to declare Contributions: BdPC designed the study, wrote the initial draft and conducted formal analyses. JdPC and RAR helped conceptualizing the idea and critically reviewed the manuscript. DM, JP, and SC critically reviewed the manuscript and provided input. All authors contributed to and have approved the final manuscript. Acknowledgements: None. Role of funding source: D. McGregor and J. Palarea-Albaladejo have been supported by the Scottish Government’s Rural and Environment Science and Analytical Services Division (RESAS). J. PalareaAlbaladejo has also been supported by the Spanish Ministry of Economy and Competitiveness under the project CODA-RETOS MTM2015-65016-C2-1(2)-R
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Figure legends: Figure 1. Estimated reduction in depression symptoms (as measured by the PHQ-9 depression score scale) associated with reallocating time from sedentary behaviour to another behaviour (Light intensity physical activity, Moderate-to-vigorous physical activity, and Sleep) from the mean overall composition of (589.05, 304.85, 14.57, 531.51). The green line in the figure represents the theoretical change in depression symptom scores (PHQ-9) from replacing time spent in sedentary behaviour with time spent in Moderate-to-vigorous physical activity. For example, replacing 60 minutes of sedentary time with 60 minutes Moderate-tovigorous physical activity would result in a reduction of -0.09 points in depression symptoms.
Table 1. Descriptive characteristics of the sample (n= 3,233) Age (yr.) Gender, female, % Body Mass Index (Kg/m2) Current smokers, %
47.43 (19.45) 52.1 28.58 (6.74) 21.6
Depression symptoms (PHQ-9)
2.51 (3.38)
At least 1 chronic condition, %
39.3
Sleep (%)*
36.19
Sedentary behaviour (%)*
40.47
Light intensity physical activity (%)*
21.45
Moderate-to-vigorous physical activity (%)*
1.88
Values are arithmetic mean (SD) unless otherwise stated. *Geometric mean normalized to 100% of time. PHQ-9: Patient Health Questionnaire-9 items