Physical activity and sedentary behavior as multimorbidity discriminators among elderly Brazilians
a cross-sectional study
Keywords:
Healthy lifestyle, Exercise, Sedentary behavior, Chronic disease, EpidemiologyAbstract
BACKGROUND: Associations between behaviors and individual chronic diseases have been demonstrated. However, the relationship between time spent on sedentary behavior and multimorbidity remains less clear. OBJECTIVE: To identify the predictive power of various intensities of physical activity versus sedentary behavior, as discriminatory factors for cardiometabolic multimorbidity (cardiovascular diseases and diabetes) in the elderly. DESIGN AND SETTING: Cross-sectional study in different residential census tracts and residential households in Florianópolis (SC). METHODS: The participants were 425 elderly people (65% women) from the EpiFloripa Aging study in 2014. Sociodemographic variables and self-reported incidence of cardiovascular diseases and diabetes were obtained via a questionnaire. Light physical activity (LPA), moderate-to-vigorous physical activity (MVPA) and sedentary behavior (SB) were measured using accelerometers. The analyses were stratified according to sex and included a diagnosis for interpretation. Behaviors were taken into consideration if their predictive power in terms of area under the receiver operating characteristic (ROC) curve was greater than 0.50. The time cutoff point was defined from sensitivity and specificity. RESULTS: For older adult men with diabetes, the predictive value of MVPA for absence of multimorbidity was an area of 0.75 (95% confidence interval, CI: 0.538-0.962), and a cutoff of 17 minutes per day. Older adult women with diabetes had an area of 0.71 (95% CI: 0.524-0.866) and a cutoff of 10 minutes per day. LPA and SB did not present predictive values. CONCLUSION: The time spent on MVPA is a predictor of absence of multimorbidity in elderly people with diabetes, for both sexes.
Downloads
References
Bähler C, Huber CA, Brüngger B, Reich O. Multimorbidity, health care utilization and costs in an elderly community-dwelling population: a claims data based observational study. BMC Health Serv Res. 15:23. PMID: 25609174; https://doi.org/10.1186/s12913-015-0698-2.
Violan C, Foguet-Boreu Q, Flores-Mateo G, et al. Prevalence, determinants and patterns of multimorbidity in primary care: a systematic review of observational studies. PLoS One. 2014;9(7):e102149. PMID: 25048354; https://doi.org/10.1371/journal.pone.0102149.
Melo-Silva AM, Mambrini JVM, Souza Junior PRB, Andrade FB, Lima-Costa MF. Hospitalizations among older adults: results from ELSI-Brazil. Rev Saude Publica. 2018;52Suppl 2(Suppl 2):3s. PMID: 30379289; https://doi.org/10.11606/s1518-8787.2018052000639.
Qiu M, Shen W, Song X, et al. Effects of prediabetes mellitus alone or plus hypertension on subsequent occurrence of cardiovascular disease and diabetes mellitus: longitudinal study. Hypertension. 2015;65(3):525-30. PMID: 25624343; https://doi.org/10.1161/HYPERTENSIONAHA.114.04632.
Sepanlou SG, Sharafkhah M, Poustchi H, et al. Hypertension and mortality in the Golestan Cohort Study: A prospective study of 50 000 adults in Iran. J Hum Hypertens. 2016;30(4):260-7. PMID: 26063561; https://doi.org/10.1038/jhh.2015.57.
Moreira B de S, Sampaio RF, Furtado SB, Dias RC, Kirkwood RN. The Relationship Between Diabetes Mellitus, Geriatric Syndromes, Physical Function, and Gait: A Review of the Literature. Curr Diabetes Rev. 2016;12(3):240-51. https://doi.org/10.2174/1573399811666150615142746.
World Health Organization. Global strategy on diet, physical activity and health. Geneva: WHO; 2004. Available from: https://www.who.int/dietphysicalactivity/strategy/eb11344/strategy_english_web.pdf Accessed in 2020 (Nov 25).
Brasil. Ministério da Saúde. Secretaria de Vigilância em Saúde. Departamento de Análise de Situação de Saúde. Plano de ações estratégicas para o enfrentamento das doenças crônicas não transmissíveis (DCNT) no Brasil: 2011-2022. Brasília, DF: Ministério da Saúde; 2011. Available from: https://portaldeboaspraticas.iff.fiocruz.br/biblioteca/plano-de-acoes-estrategicas-para-o-enfrentamento-das-doencas-cronicas/ Accessed in 2020 (Nov 25).
Bann D, Hire D, Manini T, et al. Light intensity physical activity and sedentary behavior in relation to body mass index and grip strength in older adults: cross-sectional findings from the lifestyle interventions and independence for elders (LIFE) study. PLoS One. 2015;10(4):e0126063. PMID: 25647685; https://doi.org/10.1371/journal.pone.0116058.
Ekelund U, Steene-Johannessen J, Brown WJ, et al. Does physical activity attenuate, or even eliminate, the detrimental association of sitting time with mortality? A harmonised meta-analysis of data from more than 1 million men and women. Lancet. 2016;388(10051):1302-10. PMID: 27475271; https://doi.org/10.1016/S0140-6736(16)30370-1.
Silva PAS, Rocha SV, Vasconcelos LRC, Santos CA. Comportamento sedentário como discriminador dos transtornos mentais comuns em idosos. J Bras Psiquiatr. 2017;66(4):183-8. doi: 10.1590/0047-2085000000169
da Silva VD, Tribess S, Meneguci J, et al. Time Spent in Sedentary Behaviour as Discriminant Criterion for Frailty in Older Adults. Int J Environ Res Public Health 2018;15(7):1336. PMID: 29949848; https://doi.org/10.3390/ijerph15071336.
World Health Organization. WHO guidelines on physical activity and sedentary behaviour: at a glance. 2020. Available from: https://apps.who.int/iris/handle/10665/337001 Accessed in 2020 (Dec 16).
Leiva AM, Martínez MA, Cristi-Montero C, et al. El sedentarismo se asocia a un incremento de factores de riesgo cardiovascular y metabólicos independiente de los niveles de actividad física [Sedentary lifestyle is associated with metabolic and cardiovascular risk factors independent of physical activity]. Rev Med Chil. 2017;145(4):458-67. PMID: 28748993; https://doi.org/10.4067S0034-98872017000400006.
Ramírez-Vélez R, Pérez-Sousa MÁ, Izquierdo M, et al. Validation of Surrogate Anthropometric Indices in Older Adults: What Is the Best Indicator of High Cardiometabolic Risk Factor Clustering? Nutrients. 2019;11(8):1701. PMID: 31344803; https://doi.org/10.3390/nu11081701. Erratum in: Nutrients. 2019 Oct 10;11(10).
Pasdar Y, Moradi S, Moludi J, et al. Waist-to-height ratio is a better discriminator of cardiovascular disease than other anthropometric indicators in Kurdish adults. Sci Rep. 2020;10(1):16228. PMID: 33004896; https://doi.org/10.1038/s41598-020-73224-8
Queiroz CO, Pitanga F, Lotufo PA, et al. Amount of physical activity necessary for a normal level of high-sensitivity C-reactive protein in ELSA-Brasil: a cross-sectional study. Sao Paulo Med J. 2020;138(1):19-26. PMID: 32321101; http://dx.doi.org/10.1590/1516-3180.2019.0301.r2.20102019.
Ferrari GLDM, Kovalskys I, Fisberg M, et al. Comparison of self-report versus accelerometer – measured physical activity and sedentary behaviors and their association with body composition in Latin American countries. PLoS ONE. 2020 15(4): e0232420. PMID: 32343753; https://doi.org/10.1371/journal.pone.0232420.
Confortin SB, Schneider IJC, Antes DL, et al. Life and health conditions among elderly: results of the EpiFloripa Idoso cohort study. Epidemiol Serv Saude. 2017;26(2):305-17. PMID: 28492772; https://doi.org10.5123/S1679-49742017000200008.
Schneider IJC, Confortin SC, Bernardo CO, et al. EpiFloripa Aging cohort study: methods, operational aspects, and follow-up strategies. Rev Saude Publica. 2017;51:104. PMID: 29166443; https://doi.org/10.11606/S1518-8787.2017051006776.
Choi L, Liu Z, Matthews CE, Buchowski MS. Validation of accelerometer wear and nonwear time classification algorithm. Med Sci Sports Exerc. 2011;43(2):357-64. PMID: 20581716; https://doi.org/10.1249/MSS.0b013e3181ed61a3.
Freedson PS, Melanson E, Sirard J. Calibration of the Computer Science and Applications, Inc. accelerometer. Med Sci Sports Exerc. 1998;30(5):777-81. PMID: 9588623; https://doi.org/10.1097/00005768-199805000-00021.
Erdreich LS, Lee ET. Use of relative operating characteristic analysis in epidemiology. A method for dealing with subjective judgement. Am J Epidemiol. 1981;114(5):649-62. PMID: 7304595; https://doi.org/10.1093/oxfordjournals.aje.a113236.
Schisterman EF, Faraggi D, Reiser B, Trevisan M. Statistical inference for the area under the receiver operating characteristic curve in the presence of random measurement error. Am J Epidemiol. 2001;154(2):174-9. https://doi.org/10.1093/aje/154.2.174.
Moore GE, Durstine JL, Painter P. ACSM’s exercise management for persons with chronic diseases and disabilities - 4th edition. Champaign, IL: Human Kinetics; 2016.
Santos A de L, Cecílio HP, Teston EF, et al. Microvascular complications in type 2 diabetes and associated factors: a telephone survey of self-reported morbidity. Cien Saude Colet. 2015;20(3):761-70. PMID: 25760116; https://doi.org/10.1590/1413-81232015203.12182014.
Dhalwani NN, Zaccardi F, O’Donovan G, et al. Association Between Lifestyle Factors and the Incidence of Multimorbidity in an Older English Population. J Gerontol A Biol Sci Med Sci. 2017;72(4):528-34. PMID: 27470302; https://doi.org/10.1093/gerona/glw146.
Williams JS, Egede LE. The Association Between Multimorbidity and Quality of Life, Health Status and Functional Disability. Am J Med Sci. 2016;352(1):45-52. PMID: 27432034; https://doi.org/10.1016/j.amjms.2016.03.004.
Oja P, Kelly P, Murtagh EM, et al. Effects of frequency, intensity, duration and volume of walking interventions on CVD risk factors: a systematic review and meta-regression analysis of randomised controlled trials among inactive healthy adults. Br J Sports Med. 2018;52(12):769-75. PMID: 29858464; https://doi.org/10.1136/bjsports-2017-098558.
Marques A, Santos DA, Peralta M, Sardinha LB, González Valeiro M. Regular physical activity eliminates the harmful association of television watching with multimorbidity. A cross-sectional study from the European Social Survey. Prev Med. 2018;109:28-33. PMID: 29360480; https://doi.org/10.1016/j.ypmed.2018.01.015.
Pelclová J, Štefelová N, Hodonská J, et al. Reallocating Time from Sedentary Behavior to Light and Moderate-to-Vigorous Physical Activity: What Has a Stronger Association with Adiposity in Older Adult Women? Int J Environ Res Public Health. 2018;15(7):1444. PMID: 29987233; https://doi.org/10.3390/ijerph15071444.
Dhalwani NN, O’Donovan G, Zaccardi F, et al. Long terms trends of multimorbidity and association with physical activity in older English population. Int J Behav Nutr Phys Act. 2016;13:8. PMID: 26785753; https://doi.org./10.1186/s12966-016-0330-9.
United Nations Development Programme. Human Development Report 2015: Work for Human Development. New York: United Nations Development Programme; 2015. Available from: http://hdr.undp.org/sites/default/files/2015_human_development_report.pdf Accessed in 2020 (Nov 25).