medigraphic.com
Instituto Nacional de Salud Pública

2023, Number 5

<< Back Next >>

salud publica mex 2023; 65 (5)

Motoric cognitive risk syndrome and its association with falls: a secondary analysis of the Mexican Health and Aging Study

Márquez I, Carrillo-Vega MF, Pérez-Zepeda MU, Cano-Gutiérrez C

Language: Spanish
References: 24
Page: 523-529
PDF size: 278.68 Kb.


ABSTRACT

Objective. To reveal whether motoric cognitive risk syndrome (MCR) is associated with falls, recurrent falls, and complicated falls in older Mexican adults. Materials and methods. This is a secondary analysis of the Mexican Health and Aging Study. MCR was assessed in 2012 and included fall-related outcomes (recurrent [≥2], complicated [need for medical treatment] and number) in the 2018 follow-up. Competing risks analysis was performed, and subhazard ratios (sHRs) were estimated, adjusting for different variables. Negative binomial regression was used to estimate the incidence rate ratio (IRR) of the number of falls. Results. A total of 1 929 participants were included, with a median age of 62 years and 58.3% female. The prevalence of MCR was 17.4% and was associated with falls sHR 1.11 (95%CI: 1.11,1.12), recurrent falls sHR 1.16 (95%CI: 1.15,1.16) and complicated falls sHR 1.25 (95%CI: 1.24,1.25). The number of falls was also independently associated with baseline MCR (IRR 1.19; 95% CI 1.01,1.40; p=0.039). Conclusion. MCR is independently associated with falls. Increasing the evidence on how MCR anticipates burdensome problems in older adults could lead to actions to halt them; therefore, including it in screening assessments could be clinically useful.


REFERENCES

  1. Carpenter CR, Cameron A, Ganz DA, Liu S. Older adult falls inemergency medicine-a sentinel event. Clin Geriatr Med. 2018;34(3):355-67. https://doi.org/10.1016/j.cger.2018.04.002

  2. Dautzenberg L, Beglinger S, Tsokani S, Zevgiti S, Raijmann R, RodondiN, et al. Interventions for preventing falls and fall-related fractures incommunity-dwelling older adults: A systematic review and network metaanalysis.J Am Geriatr Soc. 2021;69(10):2973-84. https://doi.org/10.1111/jgs.17375

  3. Shi J, Zhou BY, Tao YK, Yu PL, Zhang CF, Qin ZH, et al. Incidence andassociated factors for single and recurrent falls among the elderly in anurban community of Beijing. Biomed Environ Sci. 2014;27:939-49. https://doi.org/10.3967/bes2014.134

  4. Tinetti ME, Inouye SK, Gill TM, Doucette JT. Shared risk factors forfalls, incontinence, and functional dependence. Unifying the approach togeriatric syndromes. Jama. 1995;273(17):1348-53. Available from: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=7715059

  5. Li Y, Hou L, Zhao H, Xie R, Yi Y, Ding X. Risk factors for falls amongcommunity-dwelling older adults: A systematic review and meta-analysis.Front Med. 2022;9:1019094. https://doi.org/10.3389/fmed.2022.1019094

  6. Ruiz-Ruiz L, Jimenez AR, Garcia-Villamil G, Seco F. Detecting fall riskand frailty in elders with inertial motion sensors: a survey of significantgait parameters. Sensors. 2021;21(20):6918. https://doi.org/10.3390/s21206918

  7. Inoue T, Kamijo K, Haraguchi K, Suzuki A, Noto M, Yamashita Y, et al.Risk factors for falls in terms of attention during gait in communitydwellingolder adults. Geriatr Gerontol Int. 2018;18:1267-71. https://doi.org/10.1111/ggi.13462

  8. Udina C, Ayers E, Inzitari M, Verghese J. Walking while talking andprefrontal oxygenation in motoric cognitive risk syndrome: clinical andpathophysiological aspects. J Alzheimers Dis. 2021;84:1585-96. https://doi.org/10.3233/JAD-210239

  9. Maggio M, Lauretani F. Prevalence, incidence, and clinical impact ofcognitive-motoric risk syndrome in Europe, USA, and Japan: facts andnumbers update 2019. J Cachexia Sarcopenia Muscle. 201;10:953-5.https://doi.org/10.1002/jcsm.12476

  10. Verghese J, Wang C, Lipton RB, Holtzer R. Motoric cognitive risksyndrome and the risk of dementia. J Gerontol A Biol Sci Med Sci.2013;68(4):412-8.

  11. Verghese J, Annweiler C, Ayers E, Barzilai N, Beauchet O, BennettDA, et al. Motoric cognitive risk syndrome: multicountry prevalenceand dementia risk. Neurology. 2014;83:718-26. https://doi.org/10.1212/WNL.0000000000000717

  12. Aguilar-Navarro SG, Mimenza-Alvarado AJ, Aguilar-Esquivel JE, Yeverino-Castro SG, Juarez-Cedillo T, Mejia-Arango S. Motoric cognitive risksyndrome: Prevalence and Risk of cognitive impairment in a populationstudied in the Mexican Health and Aging Study 2012-2015. J Nutr HealthAging. 2019;23:227-31. https://doi.org/10.1007/s12603-019-1160-7

  13. Lu WW, Liu BZ, Lv MZ, Tu JK, Kang ZR, Hu RP, et al. Associationbetween motoric cognitive risk syndrome and future falls among Chinesecommunity-dwelling elderly: A nationwide cohort study. Brain Behav.2023:e3044. https://doi.org/10.1002/brb3.3044

  14. Beauchet O, Sekhon H, Schott A-M, Rolland Y, Muir-Hunter S, Markle-Reid M, et al. Motoric cognitive risk syndrome and risk for falls, theirrecurrence, and postfall fractures: results from a prospective observationalpopulation-based cohort study. J Am Med Dir Assoc. 2019;20:1268-73.https://doi.org/10.1016/j.jamda.2019.04.021

  15. Callisaya ML, Ayers E, Barzilai N, Ferrucci L, Guralnik JM, Lipton RB, etal. Motoric cognitive risk syndrome and falls risk: a multi-center study. JAlzheimers Dis. 2016;53:1043-52. https://doi.org/10.3233/JAD-160230

  16. Wong R, Michaels-Obregon A, Palloni A. Cohort profile: The MexicanHealth and Aging Study (MHAS). Int J Epidemiol. 2017;46:e2. https://doi.org/10.1093/ije/dyu263

  17. Pérez-Zepeda MU, González-Chavero JG, Salinas-Martínez R,Gutiérrez-Robledo LM. Risk factors for slow gait speed: a nested casecontrolsecondary analysis of the Mexican Health and aging study. Journalof Frailty and Aging. 2015;4. https://doi.org/10.14283/jfa.2015.63

  18. Mejia-Arango S, Wong R, Michaels-Obregon A. Normative andstandardized data for cognitive measures in the Mexican Health and AgingStudy. Salud Publica Mex. 2015;57:S90-6. https://doi.org/10.21149/spm.v57s1.7594

  19. Ho ISS, Azcoaga-Lorenzo A, Akbari A, Davies J, Khunti K,Kadam UT, et al. Measuring multimorbidity in research: Delphiconsensus study. BMJ Med. 2022;1:e000247. https://doi.org/10.1136/bmjmed-2022-000247

  20. Grande G, Triolo F, Nuara A, Welmer AK, Fratiglioni L, VetranoDL. Measuring gait speed to better identify prodromal dementia. ExpGerontol. 2019;124:110625. https://doi.org/10.1016/j.exger.2019.05.014

  21. Meiner Z, Ayers E, Verghese J. Motoric cognitive risk syndrome: a riskfactor for cognitive impairment and dementia in different populations. AnnGeriatr Med Res. 2020;24:3-14. https://doi.org/ 10.4235/agmr.20.0001

  22. Faes MC, Reelick MF, Esselink RA, Rikkert MG. Developing andevaluating complex healthcare interventions in geriatrics: the use ofthe medical research council framework exemplified on a complex fallprevention intervention. J Am Geriatr Soc. 2010;58:2212-21. https://doi.org/10.1111/j.1532-5415.2010.03108.x

  23. Company-Sancho MC, Alonso-Poncelas E, Rich-Ruiz M, Cidoncha-Moreno MA, Gonzalez-Pisano A, Abad-Corpa E, et al. The relationbetween functional performance, falls and previous falls amongparticipants in the Otago Programme: A secondary data analysis. Int JEnviron Res Public Health. 2021;18(12):6501. https://doi.org/10.3390/ijerph18126501

  24. Scott D, Johansson J, Gandham A, Ebeling PR, Nordstrom P, NordstromA. Associations of accelerometer-determined physical activity andsedentary behavior with sarcopenia and incident falls over 12 months incommunity-dwelling Swedish older adults. J Sport Health Sci. 2021;10:577-84. https://doi.org/10.1016/j.jshs.2020.01.006




2020     |     www.medigraphic.com