Associations of self-reported physical activity and depression in 10,000 Irish adults across harmonised datasets: a DEDIPAC-study

Cillian Mc Dowell, Angela Carlin, Laura Capranica, Christina Dillon, Janas Harrington, Jeroen Lakerveld, Anne Loyen, Fiona Chun Man Ling, Johannes Brug, Ciaran MacDonncha, Matthew Herring

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

Background Depression is a prevalent, debilitating, and often recurrent mood disorder for which successful first-line treatments remains limited. The purpose of this study was to investigate the cross-sectional associations between self-reported physical activity (PA) and depressive symptoms and status among Irish adults, using two existing datasets, The Irish Longitudinal Study on Ageing (TILDA) and The Mitchelstown Cohort Study. Methods The two selected databases were pooled (n = 10,122), and relevant variables were harmonized. PA was measured using the short form International Physical Activity Questionnaire. Depressive symptoms were measured by the Center for Epidemiologic Studies Depression (CES-D) questionnaire. Participants were classified as meeting World Health Organization moderate-to-vigorous PA (MVPA) guidelines or not, and divided into tertiles based on weekly minutes of MVPA. A CES-D score of ≥16 indicated elevated depressive symptoms. Data collection were conducted in 2010–2011. Results Significantly higher depressive symptoms were reported by females (7.11 ± 7.87) than males (5.74 ± 6.86; p < 0.001). Following adjustment for age, sex, BMI, and dataset, meeting the PA guidelines was associated with 44.7% (95%CI: 35.0 to 52.9; p < 0.001) lower odds of elevated depressive symptoms. Compared to the low PA tertile, the middle and high PA tertiles were associated with 25.2% (95%CI: 8.7 to 38.6; p < 0.01) and 50.8% (95%CI: 40.7 to 59.2; p < 0.001) lower odds of elevated depressive symptoms, respectively. Conclusion Meeting the PA guidelines is associated with lower odds of elevated depressive symptoms, and increased volumes of MVPA are associated with lower odds of elevated depressive symptoms.
LanguageEnglish
JournalBMC Public Health
DOIs
Publication statusPublished - 1 Jul 2018

Fingerprint

Exercise
Depression
Guidelines
Epidemiologic Studies
Datasets
Mood Disorders
Longitudinal Studies
Cohort Studies
Databases

Keywords

  • Physical Activity
  • Mental Health
  • Elderly
  • Ireland
  • Cross-Sectional Studies

Cite this

Mc Dowell, Cillian ; Carlin, Angela ; Capranica, Laura ; Dillon, Christina ; Harrington, Janas ; Lakerveld, Jeroen ; Loyen, Anne ; Ling, Fiona Chun Man ; Brug, Johannes ; MacDonncha, Ciaran ; Herring, Matthew. / Associations of self-reported physical activity and depression in 10,000 Irish adults across harmonised datasets: a DEDIPAC-study. In: BMC Public Health. 2018.
@article{0a11335394af4912999c3c6f642e2654,
title = "Associations of self-reported physical activity and depression in 10,000 Irish adults across harmonised datasets: a DEDIPAC-study",
abstract = "Background Depression is a prevalent, debilitating, and often recurrent mood disorder for which successful first-line treatments remains limited. The purpose of this study was to investigate the cross-sectional associations between self-reported physical activity (PA) and depressive symptoms and status among Irish adults, using two existing datasets, The Irish Longitudinal Study on Ageing (TILDA) and The Mitchelstown Cohort Study. Methods The two selected databases were pooled (n = 10,122), and relevant variables were harmonized. PA was measured using the short form International Physical Activity Questionnaire. Depressive symptoms were measured by the Center for Epidemiologic Studies Depression (CES-D) questionnaire. Participants were classified as meeting World Health Organization moderate-to-vigorous PA (MVPA) guidelines or not, and divided into tertiles based on weekly minutes of MVPA. A CES-D score of ≥16 indicated elevated depressive symptoms. Data collection were conducted in 2010–2011. Results Significantly higher depressive symptoms were reported by females (7.11 ± 7.87) than males (5.74 ± 6.86; p < 0.001). Following adjustment for age, sex, BMI, and dataset, meeting the PA guidelines was associated with 44.7{\%} (95{\%}CI: 35.0 to 52.9; p < 0.001) lower odds of elevated depressive symptoms. Compared to the low PA tertile, the middle and high PA tertiles were associated with 25.2{\%} (95{\%}CI: 8.7 to 38.6; p < 0.01) and 50.8{\%} (95{\%}CI: 40.7 to 59.2; p < 0.001) lower odds of elevated depressive symptoms, respectively. Conclusion Meeting the PA guidelines is associated with lower odds of elevated depressive symptoms, and increased volumes of MVPA are associated with lower odds of elevated depressive symptoms.",
keywords = "Physical Activity, Mental Health, Elderly, Ireland, Cross-Sectional Studies",
author = "{Mc Dowell}, Cillian and Angela Carlin and Laura Capranica and Christina Dillon and Janas Harrington and Jeroen Lakerveld and Anne Loyen and Ling, {Fiona Chun Man} and Johannes Brug and Ciaran MacDonncha and Matthew Herring",
note = "World Health Organization, 2017. Depression: A Global Public Health Concern. World Health Organization, Geneva. Available at: http://www.who.int/mediacentre/factsheets/fs369/en/. Accessed on Feb. 22 2018. 2.Kessler RC, Petukhova M, Sampson NA, Zaslavsky AM, Wittchen HU. Twelve-month and lifetime prevalence and lifetime morbid risk of anxiety and mood disorders in the United States. Int J Methods Psychiatr Res. 2012;21:169–84.View ArticlePubMedPubMed CentralGoogle Scholar 3.Ferrari AJ, Charlson FJ, Norman RE, Patten SB, Freedman G, Murray CJ, et al. Burden of depressive disorders by country, sex, age, and year: findings from the global burden of disease study 2010. PLoS Med. 2013;10(11)Google Scholar 4.Olesen J, Gustavsson A, Svensson M, Wittchen HU, J{\"o}nsson B. The economic cost of brain disorders in Europe. Eur J Neurol. 2012;19(1):155–62.View ArticlePubMedGoogle Scholar 5.Trivedi MH, Rush AJ, Wisniewski SR, Nierenberg AA, Warden D, Ritz L, et al. Evaluation of outcomes with citalopram for depression using measurement-based care in STAR* D: implications for clinical practice. Am J Psychiatry. 2006;163:28–40.View ArticlePubMedGoogle Scholar 6.Gordon BR, McDowell CP, Hallgren M, Meyer JD, Lyons M, Herring MP. Association of Efficacy of resistance exercise training with depressive symptoms: meta-analysis and meta-regression analysis of randomized clinical trials. JAMA Psychiatry. 2018; https://doi.org/10.1001/jamapsychiatry.2018.0572. 7.Schuch FB, Vancampfort D, Richards J, Rosenbaum S, Ward PB, Stubbs B. Exercise as a treatment for depression: a meta-analysis adjusting for publication bias. Psychiatry Res. 2016;77:42–51.View ArticleGoogle Scholar 8.Forsell Y. The pathway to meeting need for mental health services in Sweden. Psych Serv. 2006;57(1):114–9.View ArticleGoogle Scholar 9.Physical Activity Guidelines Advisory Committee. Physical activity guidelines advisory committee report, 2008. Washington, DC: US: Department of Health and Human Services 2008; 2008. p. A1–H14.Google Scholar 10.Schuch FB, Vancampfort D, Rosenbaum S, Richards J, Ward PB, Stubbs B. Exercise improves physical and psychological quality of life in people with depression: a meta-analysis including the evaluation of control group response. Psychiatry Res. 2016;241:47–54.View ArticlePubMedGoogle Scholar 11.Burton C, McKinstry B, Tătar AS, Serrano-Blanco A, Pagliari C, Wolters M. Activity monitoring in patients with depression: a systematic review. J Affect Disord. 2013;145(1):21–8.View ArticlePubMedGoogle Scholar 12.Helgad{\'o}ttir B, Forsell Y, Ekblom {\"O}. Physical activity patterns of people affected by depressive and anxiety disorders as measured by accelerometers: a cross-sectional study. PLoS One. 2015;10(1)Google Scholar 13.Mammen G, Faulkner G. Physical activity and the prevention of depression: a systematic review of prospective studies. Am J Prev Med. 2013;45(5):649–57.View ArticlePubMedGoogle Scholar 14.Schuch FB, Vancampfort D, Firth J, Rosenbaum S, Ward PB, Silva ES, Hallgren M, et al. Physical activity and incident depression: a meta-analysis of prospective cohort studies. Am J Psychiatry. 2018; https://doi.org/10.1176/appi.ajp.2018.17111194. 15.Hallgren M, Nakitanda OA, Ekblom {\"O}, Herring MP, Owen N, Dunstan D, et al. Habitual physical activity levels predict treatment outcomes in depressed adults: a prospective cohort study. Prev Med. 2016;88:53–8.View ArticlePubMedGoogle Scholar 16.Artaud F, Dugravot A, Sabia S, Singh-Manoux A, Tzourio C, Elbaz A. Unhealthy behaviours and disability in older adults: Three-City Dijon cohort study. BMJ. 2013;347Google Scholar 17.Doiron D, Burton P, Marcon Y, Gaye A, Wolffenbuttel BH, Perola M, et al. Data harmonization and federated analysis of population-based studies: the BioSHaRE project. Emerg Themes Epidemiol. 2013;10(1):1.View ArticleGoogle Scholar 18.Pisani E, AbouZahr C. Sharing health data: good intentions are not enough. Bull World Health Organ. 2010;88(6):462–6.View ArticlePubMedPubMed CentralGoogle Scholar 19.Wilkinson MD, Dumontier M, Aalbersberg IJ, Appleton G, Axton M, Baak A, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3:160018. https://doi.org/10.1038/sdata.2016.18. 20.Buffart LM, Kalter J, Chinapaw MJ, Heymans MW, Aaronson NK, Courneya KS, et al. Predicting OptimaL cAncer RehabIlitation and supportive care (POLARIS): rationale and design for meta-analyses of individual patient data of randomized controlled trials that evaluate the effect of physical activity and psychosocial interventions on health-related quality of life in cancer survivors. Syst Rev. 2013;2(1):1.View ArticleGoogle Scholar 21.Schaap LA, Peeters GM, Dennison EM, Zambon S, Nikolaus T, Sanchez-Martinez M, et al. European project on OSteoArthritis (EPOSA): methodological challenges in harmonization of existing data from five European population-based cohorts on aging. BMC Musculoskelet Disord. 2011;12(1):1.View ArticleGoogle Scholar 22.Fortier I, Doiron D, Little J, Ferretti V, L’Heureux F, Stolk RP, et al. Is rigorous retrospective harmonization possible? Application of the DataSHaPER approach across 53 large studies. Int J Epidemiol. 2011;40(5):1314–28.View ArticlePubMedPubMed CentralGoogle Scholar 23.Horwood LJ, Fergusson DM, Coffey C, Patton GC, Tait R, Smart D, et al. Cannabis and depression: an integrative data analysis of four Australasian cohorts. Drug Alcohol Depend. 2012;126(3):369–78.View ArticlePubMedGoogle Scholar 24.Fortier I, Raina P, Van den Heuvel ER, Griffith LE, Craig C, Saliba M, et al. Maelstrom research guidelines for rigorous retrospective data harmonization. Int J Epidemiol. 2017;46(1):103–5.PubMedGoogle Scholar 25.Gallacher JE. The case for large scale fungible cohorts. Eur J Pub Health. 2007;17(6):548–9.View ArticleGoogle Scholar 26.Hutchinson DM, Silins E, Mattick RP, Patton GC, Fergusson DM, Hayatbakhsh R, et al. How can data harmonisation benefit mental health research? An example of the Cannabis cohorts research consortium. Aust N Z J Psychiatry. 2015;Google Scholar 27.Von Elm E, Altman DG, Egger M, Pocock SJ, G{\o}tzsche PC, Vandenbroucke JP. The strengthening the reporting of observational studies in epidemiology [STROBE] statement: guidelines for reporting observational studies. Gac Sanit. 2008;22(2):144–50.View ArticlePubMedGoogle Scholar 28.Lakerveld J, Van Der Ploeg HP, Kroeze W, Ahrens W, Allais O, Andersen LF, et al. Towards the integration and development of a cross-European research network and infrastructure: the DEterminants of DIet and physical ACtivity (DEDIPAC) knowledge hub. Int J Behav Nutr Phys Act. 2014;11(1):1.View ArticleGoogle Scholar 29.Brug J, van der Ploeg HP, Loyen A, Ahrens W, Allais O, Andersen LF, et al. Determinants of diet and physical activity (DEDIPAC): a summary of findings. Int J Behav Nutr Phys Act. 2017;14(1):150.View ArticlePubMedPubMed CentralGoogle Scholar 30.Lakerveld J, Loyen A, Ling F, De Craemer M, van der Ploeg HP, O’Gorman DJ, Carlin A, Capranica L, Kalter J, Oppert J-M, Chastin S, Cardon G, Brug J, MacDonncha C.. Identifying and sharing data for secondary data analysis of physical activity, sedentary behaviour and their determinants across the life course in Europe: general principles and an example from DEDIPAC. BMJ Open (In Press).Google Scholar 31.Kearney PM, Cronin H, O'Regan C, Kamiya Y, Savva GM, Whelan B, et al. Cohort profile: the Irish longitudinal study on ageing. Int J Epidemiol. 2011;40(4):877–84.View ArticlePubMedGoogle Scholar 32.Craig CL, Marshall AL, Sj{\"o}str{\"o}m M, Bauman AE, Booth ML, Ainsworth BE, et al. International physical activity questionnaire: 12-country reliability and validity. Med Sci Sports Exerc. 2003;35(8):1381–95.View ArticlePubMedGoogle Scholar 33.Radloff LS. The CES-D scale. a self-report depression scale for research in the general population Appl Psychol Meas. 1977;1(3):385–401.Google Scholar 34.Kearney PM, Harrington JM, Mc Carthy VJ, Fitzgerald AP, Perry IJ. Cohort profile: the Cork and Kerry diabetes and heart disease study. Int J Epidemiol. 2013;42(5):1253–62.View ArticlePubMedGoogle Scholar 35.International Physical Activity Questionnaire. Guidelines for Data Processing and Analysis of the International Physical Activity Questionnaire-Short and Long Forms; 2004. Available from: http://www.sdp.univ.fvg.it/sites/default/files/IPAQ_English_self-admin_short.pdf. 36.World Health Organization. Global recommendations on physical activity for health. 2010. Available at: www.who.int/dietphysicalactivity/factsheet_recommendations/en/. Accessed on 10/10/2017. 37.Beekman AT, Deeg DJH, Van Limbeek J, Braam AW, De Vries MZ, Van Tilburg W. Brief communication.: criterion validity of the Center for Epidemiologic Studies Depression scale (CES-D): results from a community-based sample of older subjects in the Netherlands. Psychol Med. 1997;27(1):231–5.View ArticlePubMedGoogle Scholar 38.World Health Organization. Obesity: preventing and managing the global epidemic. Geneva: WHO Tech Rep Ser 894; 2000. p. 252. Available at: http://www.who.int/nutrition/publications/obesity/WHO_TRS_894/en/. Accessed on 10/10/2017. 39.Sharpe D. Your chi-square test is statistically significant: now what? Pract Assess Res Eval. 2015;20(8):2–10.Google Scholar 40.Cumming G. The new statistics why and how. Psychol Sci. 2013;Google Scholar 41.Cohen J. A power primer. Psychol Bull. 1992;112(1):155.View ArticlePubMedGoogle Scholar 42.Cortis C, Puggina A, Pesce C, Aleksovska K, Buck C, Burns C, et al. Psychological determinants of physical activity across the life course: a{"} DEterminants of DIet and physical ACtivity{"}(DEDIPAC) umbrella systematic literature review. PLoS One. 2017;12(8)Google Scholar 43.McDowell CP, Gordon BR, Herring MP. Sex-related differences in the association between grip strength and depression: results from the Irish longitudinal study on ageing. Exp Gerontol. 2018; https://doi.org/10.1016/j.exger.2018.02.010. 44.McDowell CP, Campbell MJ, Herring MP. Sex-related differences in mood responses to acute aerobic exercise. Med Sci Sports Exerc. 2016;48(9):1798–802.View ArticlePubMedGoogle Scholar 45.Stubbs B, Koyanagi A, Schuch F, Firth J, Rosenbaum S, Veronese N, et al. Physical activity and depression: a large cross-sectional, population-based study across 36 low-and middle-income countries. Acta Psychiat Scand. 2016;134(6):546–56.View ArticlePubMedGoogle Scholar 46.Dunn AL, Trivedi MH, Kampert JB, Clark CG, Chambliss HO. Exercise treatment for depression. efficacy and dose response Am J Prev Med. 2005;28(1):1–8.View ArticlePubMedGoogle Scholar 47.Loprinzi PD. Objectively measured light and moderate-to-vigorous physical activity is associated with lower depression levels among older US adults. Aging Ment Health. 2013;17(7):801–5.View ArticlePubMedGoogle Scholar 48.Winckers AN, Mackenbach JD, Compernolle S, Nicolaou M, van der Ploeg HP, De Bourdeaudhuij I, et al. Educational differences in the validity of self-reported physical activity. BMC Public Health. 2015;15(1):1299.View ArticlePubMedPubMed CentralGoogle Scholar",
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Mc Dowell, C, Carlin, A, Capranica, L, Dillon, C, Harrington, J, Lakerveld, J, Loyen, A, Ling, FCM, Brug, J, MacDonncha, C & Herring, M 2018, 'Associations of self-reported physical activity and depression in 10,000 Irish adults across harmonised datasets: a DEDIPAC-study', BMC Public Health. https://doi.org/10.1186/s12889-018-5702-4

Associations of self-reported physical activity and depression in 10,000 Irish adults across harmonised datasets: a DEDIPAC-study. / Mc Dowell, Cillian; Carlin, Angela; Capranica, Laura; Dillon, Christina; Harrington, Janas ; Lakerveld, Jeroen ; Loyen, Anne ; Ling, Fiona Chun Man ; Brug, Johannes ; MacDonncha, Ciaran ; Herring, Matthew.

In: BMC Public Health, 01.07.2018.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Associations of self-reported physical activity and depression in 10,000 Irish adults across harmonised datasets: a DEDIPAC-study

AU - Mc Dowell, Cillian

AU - Carlin, Angela

AU - Capranica, Laura

AU - Dillon, Christina

AU - Harrington, Janas

AU - Lakerveld, Jeroen

AU - Loyen, Anne

AU - Ling, Fiona Chun Man

AU - Brug, Johannes

AU - MacDonncha, Ciaran

AU - Herring, Matthew

N1 - World Health Organization, 2017. Depression: A Global Public Health Concern. World Health Organization, Geneva. Available at: http://www.who.int/mediacentre/factsheets/fs369/en/. Accessed on Feb. 22 2018. 2.Kessler RC, Petukhova M, Sampson NA, Zaslavsky AM, Wittchen HU. Twelve-month and lifetime prevalence and lifetime morbid risk of anxiety and mood disorders in the United States. Int J Methods Psychiatr Res. 2012;21:169–84.View ArticlePubMedPubMed CentralGoogle Scholar 3.Ferrari AJ, Charlson FJ, Norman RE, Patten SB, Freedman G, Murray CJ, et al. Burden of depressive disorders by country, sex, age, and year: findings from the global burden of disease study 2010. PLoS Med. 2013;10(11)Google Scholar 4.Olesen J, Gustavsson A, Svensson M, Wittchen HU, Jönsson B. The economic cost of brain disorders in Europe. Eur J Neurol. 2012;19(1):155–62.View ArticlePubMedGoogle Scholar 5.Trivedi MH, Rush AJ, Wisniewski SR, Nierenberg AA, Warden D, Ritz L, et al. Evaluation of outcomes with citalopram for depression using measurement-based care in STAR* D: implications for clinical practice. Am J Psychiatry. 2006;163:28–40.View ArticlePubMedGoogle Scholar 6.Gordon BR, McDowell CP, Hallgren M, Meyer JD, Lyons M, Herring MP. Association of Efficacy of resistance exercise training with depressive symptoms: meta-analysis and meta-regression analysis of randomized clinical trials. JAMA Psychiatry. 2018; https://doi.org/10.1001/jamapsychiatry.2018.0572. 7.Schuch FB, Vancampfort D, Richards J, Rosenbaum S, Ward PB, Stubbs B. Exercise as a treatment for depression: a meta-analysis adjusting for publication bias. Psychiatry Res. 2016;77:42–51.View ArticleGoogle Scholar 8.Forsell Y. The pathway to meeting need for mental health services in Sweden. Psych Serv. 2006;57(1):114–9.View ArticleGoogle Scholar 9.Physical Activity Guidelines Advisory Committee. Physical activity guidelines advisory committee report, 2008. Washington, DC: US: Department of Health and Human Services 2008; 2008. p. A1–H14.Google Scholar 10.Schuch FB, Vancampfort D, Rosenbaum S, Richards J, Ward PB, Stubbs B. Exercise improves physical and psychological quality of life in people with depression: a meta-analysis including the evaluation of control group response. Psychiatry Res. 2016;241:47–54.View ArticlePubMedGoogle Scholar 11.Burton C, McKinstry B, Tătar AS, Serrano-Blanco A, Pagliari C, Wolters M. Activity monitoring in patients with depression: a systematic review. J Affect Disord. 2013;145(1):21–8.View ArticlePubMedGoogle Scholar 12.Helgadóttir B, Forsell Y, Ekblom Ö. Physical activity patterns of people affected by depressive and anxiety disorders as measured by accelerometers: a cross-sectional study. PLoS One. 2015;10(1)Google Scholar 13.Mammen G, Faulkner G. Physical activity and the prevention of depression: a systematic review of prospective studies. Am J Prev Med. 2013;45(5):649–57.View ArticlePubMedGoogle Scholar 14.Schuch FB, Vancampfort D, Firth J, Rosenbaum S, Ward PB, Silva ES, Hallgren M, et al. Physical activity and incident depression: a meta-analysis of prospective cohort studies. Am J Psychiatry. 2018; https://doi.org/10.1176/appi.ajp.2018.17111194. 15.Hallgren M, Nakitanda OA, Ekblom Ö, Herring MP, Owen N, Dunstan D, et al. Habitual physical activity levels predict treatment outcomes in depressed adults: a prospective cohort study. Prev Med. 2016;88:53–8.View ArticlePubMedGoogle Scholar 16.Artaud F, Dugravot A, Sabia S, Singh-Manoux A, Tzourio C, Elbaz A. Unhealthy behaviours and disability in older adults: Three-City Dijon cohort study. BMJ. 2013;347Google Scholar 17.Doiron D, Burton P, Marcon Y, Gaye A, Wolffenbuttel BH, Perola M, et al. Data harmonization and federated analysis of population-based studies: the BioSHaRE project. Emerg Themes Epidemiol. 2013;10(1):1.View ArticleGoogle Scholar 18.Pisani E, AbouZahr C. Sharing health data: good intentions are not enough. Bull World Health Organ. 2010;88(6):462–6.View ArticlePubMedPubMed CentralGoogle Scholar 19.Wilkinson MD, Dumontier M, Aalbersberg IJ, Appleton G, Axton M, Baak A, et al. The FAIR guiding principles for scientific data management and stewardship. Sci Data. 2016;3:160018. https://doi.org/10.1038/sdata.2016.18. 20.Buffart LM, Kalter J, Chinapaw MJ, Heymans MW, Aaronson NK, Courneya KS, et al. Predicting OptimaL cAncer RehabIlitation and supportive care (POLARIS): rationale and design for meta-analyses of individual patient data of randomized controlled trials that evaluate the effect of physical activity and psychosocial interventions on health-related quality of life in cancer survivors. Syst Rev. 2013;2(1):1.View ArticleGoogle Scholar 21.Schaap LA, Peeters GM, Dennison EM, Zambon S, Nikolaus T, Sanchez-Martinez M, et al. European project on OSteoArthritis (EPOSA): methodological challenges in harmonization of existing data from five European population-based cohorts on aging. BMC Musculoskelet Disord. 2011;12(1):1.View ArticleGoogle Scholar 22.Fortier I, Doiron D, Little J, Ferretti V, L’Heureux F, Stolk RP, et al. Is rigorous retrospective harmonization possible? Application of the DataSHaPER approach across 53 large studies. Int J Epidemiol. 2011;40(5):1314–28.View ArticlePubMedPubMed CentralGoogle Scholar 23.Horwood LJ, Fergusson DM, Coffey C, Patton GC, Tait R, Smart D, et al. Cannabis and depression: an integrative data analysis of four Australasian cohorts. Drug Alcohol Depend. 2012;126(3):369–78.View ArticlePubMedGoogle Scholar 24.Fortier I, Raina P, Van den Heuvel ER, Griffith LE, Craig C, Saliba M, et al. Maelstrom research guidelines for rigorous retrospective data harmonization. Int J Epidemiol. 2017;46(1):103–5.PubMedGoogle Scholar 25.Gallacher JE. The case for large scale fungible cohorts. Eur J Pub Health. 2007;17(6):548–9.View ArticleGoogle Scholar 26.Hutchinson DM, Silins E, Mattick RP, Patton GC, Fergusson DM, Hayatbakhsh R, et al. How can data harmonisation benefit mental health research? An example of the Cannabis cohorts research consortium. Aust N Z J Psychiatry. 2015;Google Scholar 27.Von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP. The strengthening the reporting of observational studies in epidemiology [STROBE] statement: guidelines for reporting observational studies. Gac Sanit. 2008;22(2):144–50.View ArticlePubMedGoogle Scholar 28.Lakerveld J, Van Der Ploeg HP, Kroeze W, Ahrens W, Allais O, Andersen LF, et al. Towards the integration and development of a cross-European research network and infrastructure: the DEterminants of DIet and physical ACtivity (DEDIPAC) knowledge hub. Int J Behav Nutr Phys Act. 2014;11(1):1.View ArticleGoogle Scholar 29.Brug J, van der Ploeg HP, Loyen A, Ahrens W, Allais O, Andersen LF, et al. Determinants of diet and physical activity (DEDIPAC): a summary of findings. Int J Behav Nutr Phys Act. 2017;14(1):150.View ArticlePubMedPubMed CentralGoogle Scholar 30.Lakerveld J, Loyen A, Ling F, De Craemer M, van der Ploeg HP, O’Gorman DJ, Carlin A, Capranica L, Kalter J, Oppert J-M, Chastin S, Cardon G, Brug J, MacDonncha C.. Identifying and sharing data for secondary data analysis of physical activity, sedentary behaviour and their determinants across the life course in Europe: general principles and an example from DEDIPAC. BMJ Open (In Press).Google Scholar 31.Kearney PM, Cronin H, O'Regan C, Kamiya Y, Savva GM, Whelan B, et al. Cohort profile: the Irish longitudinal study on ageing. Int J Epidemiol. 2011;40(4):877–84.View ArticlePubMedGoogle Scholar 32.Craig CL, Marshall AL, Sjöström M, Bauman AE, Booth ML, Ainsworth BE, et al. International physical activity questionnaire: 12-country reliability and validity. Med Sci Sports Exerc. 2003;35(8):1381–95.View ArticlePubMedGoogle Scholar 33.Radloff LS. The CES-D scale. a self-report depression scale for research in the general population Appl Psychol Meas. 1977;1(3):385–401.Google Scholar 34.Kearney PM, Harrington JM, Mc Carthy VJ, Fitzgerald AP, Perry IJ. Cohort profile: the Cork and Kerry diabetes and heart disease study. Int J Epidemiol. 2013;42(5):1253–62.View ArticlePubMedGoogle Scholar 35.International Physical Activity Questionnaire. Guidelines for Data Processing and Analysis of the International Physical Activity Questionnaire-Short and Long Forms; 2004. Available from: http://www.sdp.univ.fvg.it/sites/default/files/IPAQ_English_self-admin_short.pdf. 36.World Health Organization. Global recommendations on physical activity for health. 2010. Available at: www.who.int/dietphysicalactivity/factsheet_recommendations/en/. Accessed on 10/10/2017. 37.Beekman AT, Deeg DJH, Van Limbeek J, Braam AW, De Vries MZ, Van Tilburg W. Brief communication.: criterion validity of the Center for Epidemiologic Studies Depression scale (CES-D): results from a community-based sample of older subjects in the Netherlands. Psychol Med. 1997;27(1):231–5.View ArticlePubMedGoogle Scholar 38.World Health Organization. Obesity: preventing and managing the global epidemic. Geneva: WHO Tech Rep Ser 894; 2000. p. 252. Available at: http://www.who.int/nutrition/publications/obesity/WHO_TRS_894/en/. Accessed on 10/10/2017. 39.Sharpe D. Your chi-square test is statistically significant: now what? Pract Assess Res Eval. 2015;20(8):2–10.Google Scholar 40.Cumming G. The new statistics why and how. Psychol Sci. 2013;Google Scholar 41.Cohen J. A power primer. Psychol Bull. 1992;112(1):155.View ArticlePubMedGoogle Scholar 42.Cortis C, Puggina A, Pesce C, Aleksovska K, Buck C, Burns C, et al. Psychological determinants of physical activity across the life course: a" DEterminants of DIet and physical ACtivity"(DEDIPAC) umbrella systematic literature review. PLoS One. 2017;12(8)Google Scholar 43.McDowell CP, Gordon BR, Herring MP. Sex-related differences in the association between grip strength and depression: results from the Irish longitudinal study on ageing. Exp Gerontol. 2018; https://doi.org/10.1016/j.exger.2018.02.010. 44.McDowell CP, Campbell MJ, Herring MP. Sex-related differences in mood responses to acute aerobic exercise. Med Sci Sports Exerc. 2016;48(9):1798–802.View ArticlePubMedGoogle Scholar 45.Stubbs B, Koyanagi A, Schuch F, Firth J, Rosenbaum S, Veronese N, et al. Physical activity and depression: a large cross-sectional, population-based study across 36 low-and middle-income countries. Acta Psychiat Scand. 2016;134(6):546–56.View ArticlePubMedGoogle Scholar 46.Dunn AL, Trivedi MH, Kampert JB, Clark CG, Chambliss HO. Exercise treatment for depression. efficacy and dose response Am J Prev Med. 2005;28(1):1–8.View ArticlePubMedGoogle Scholar 47.Loprinzi PD. Objectively measured light and moderate-to-vigorous physical activity is associated with lower depression levels among older US adults. Aging Ment Health. 2013;17(7):801–5.View ArticlePubMedGoogle Scholar 48.Winckers AN, Mackenbach JD, Compernolle S, Nicolaou M, van der Ploeg HP, De Bourdeaudhuij I, et al. Educational differences in the validity of self-reported physical activity. BMC Public Health. 2015;15(1):1299.View ArticlePubMedPubMed CentralGoogle Scholar

PY - 2018/7/1

Y1 - 2018/7/1

N2 - Background Depression is a prevalent, debilitating, and often recurrent mood disorder for which successful first-line treatments remains limited. The purpose of this study was to investigate the cross-sectional associations between self-reported physical activity (PA) and depressive symptoms and status among Irish adults, using two existing datasets, The Irish Longitudinal Study on Ageing (TILDA) and The Mitchelstown Cohort Study. Methods The two selected databases were pooled (n = 10,122), and relevant variables were harmonized. PA was measured using the short form International Physical Activity Questionnaire. Depressive symptoms were measured by the Center for Epidemiologic Studies Depression (CES-D) questionnaire. Participants were classified as meeting World Health Organization moderate-to-vigorous PA (MVPA) guidelines or not, and divided into tertiles based on weekly minutes of MVPA. A CES-D score of ≥16 indicated elevated depressive symptoms. Data collection were conducted in 2010–2011. Results Significantly higher depressive symptoms were reported by females (7.11 ± 7.87) than males (5.74 ± 6.86; p < 0.001). Following adjustment for age, sex, BMI, and dataset, meeting the PA guidelines was associated with 44.7% (95%CI: 35.0 to 52.9; p < 0.001) lower odds of elevated depressive symptoms. Compared to the low PA tertile, the middle and high PA tertiles were associated with 25.2% (95%CI: 8.7 to 38.6; p < 0.01) and 50.8% (95%CI: 40.7 to 59.2; p < 0.001) lower odds of elevated depressive symptoms, respectively. Conclusion Meeting the PA guidelines is associated with lower odds of elevated depressive symptoms, and increased volumes of MVPA are associated with lower odds of elevated depressive symptoms.

AB - Background Depression is a prevalent, debilitating, and often recurrent mood disorder for which successful first-line treatments remains limited. The purpose of this study was to investigate the cross-sectional associations between self-reported physical activity (PA) and depressive symptoms and status among Irish adults, using two existing datasets, The Irish Longitudinal Study on Ageing (TILDA) and The Mitchelstown Cohort Study. Methods The two selected databases were pooled (n = 10,122), and relevant variables were harmonized. PA was measured using the short form International Physical Activity Questionnaire. Depressive symptoms were measured by the Center for Epidemiologic Studies Depression (CES-D) questionnaire. Participants were classified as meeting World Health Organization moderate-to-vigorous PA (MVPA) guidelines or not, and divided into tertiles based on weekly minutes of MVPA. A CES-D score of ≥16 indicated elevated depressive symptoms. Data collection were conducted in 2010–2011. Results Significantly higher depressive symptoms were reported by females (7.11 ± 7.87) than males (5.74 ± 6.86; p < 0.001). Following adjustment for age, sex, BMI, and dataset, meeting the PA guidelines was associated with 44.7% (95%CI: 35.0 to 52.9; p < 0.001) lower odds of elevated depressive symptoms. Compared to the low PA tertile, the middle and high PA tertiles were associated with 25.2% (95%CI: 8.7 to 38.6; p < 0.01) and 50.8% (95%CI: 40.7 to 59.2; p < 0.001) lower odds of elevated depressive symptoms, respectively. Conclusion Meeting the PA guidelines is associated with lower odds of elevated depressive symptoms, and increased volumes of MVPA are associated with lower odds of elevated depressive symptoms.

KW - Physical Activity

KW - Mental Health

KW - Elderly

KW - Ireland

KW - Cross-Sectional Studies

U2 - 10.1186/s12889-018-5702-4

DO - 10.1186/s12889-018-5702-4

M3 - Article

JO - BMC Public Health

T2 - BMC Public Health

JF - BMC Public Health

SN - 1471-2458

ER -