Investigating multisite pain as a predictor of self-reported falls and falls requiring health care use in an older population: A prospective cohort study

Autoři: Victoria K. Welsh aff001;  Christian D. Mallen aff001;  Reuben Ogollah aff002;  Ross Wilkie aff001;  John McBeth aff003
Působiště autorů: Arthritis Research UK Primary Care Centre, Research Institute for Primary Care & Health Sciences, Keele University, Staffordshire, United Kingdom aff001;  Faculty of Medicine & Health Sciences, South Block, Queen’s Medical Centre, Nottingham, United Kingdom aff002;  Arthritis Research UK Centre for Epidemiology, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, United Kingdom aff003
Vyšlo v časopise: PLoS ONE 14(12)
Kategorie: Research Article


Older people are continuing to fall despite fall prevention guidelines targeting known falls’ risk factors. Multisite pain is a potential novel falls’ risk factor requiring further exploration. This study hypothesises that: (1) an increasing number of pain sites and widespread pain predicts self-reported falls and falls recorded in primary and secondary healthcare records; (2) those relationships are independent of known falls’ risk factors and putative confounders. This prospective cohort study linked data from self-completed questionnaires, primary care electronic health records, secondary care admission statistics and national mortality data. Between 2002–2005, self-completion questionnaires were mailed to community-dwelling individuals aged 50 years and older registered with one of eight general practices in North Staffordshire, UK(n = 26,129) yielding 18,497 respondents. 11,375 respondents entered the study; 4386 completed six year follow-up. Self-reported falls were extracted from three and six year follow-up questionnaires. Falls requiring healthcare were extracted from routinely collected primary and secondary healthcare data. Increasing number of pain sites increased odds of future 3 year (odds ratio 1.12 (95% confidence interval: 1.01–1.24)) and 6 year self-reported fall (odds ratio 1.02 (1.00–1.03)) and increased hazard of future fall requiring primary healthcare (hazard ratio 1.01 (1.00–1.03)). The presence of widespread pain increased odds of future 3 year (odds ratio 1.27 (0.92–1.75)) and 6 year fall (odds ratio 1.43(1.06–1.95)) and increased hazard of future fall requiring primary healthcare (hazard ratio 1.27(0.98–1.65)). Multisite pain was not associated with future fall requiring secondary care admission. Multisite pain must be included as a falls’ risk factor in guidelines to ensure clinicians identify their older patients at risk of falls and employ timely implementation of current falls prevention strategies.

Klíčová slova:

Analgesics – Electronic medical records – Hospitals – Medical risk factors – Mental health and psychiatry – Opioids – Primary care – Surveys


1. Todd C, Skelton D. What are the main risk factors for falls among older people and what are the most effective interventions to prevent these falls? Copenhagen: WHO Regional Office for Europe (Health Evidence Network report); 2004. [Cited 2018 Nov 16]. Available from

2. Panel on Prevention of Falls in Older Persons, American Geriatric Society and British Geriatrics Society. Summary of the Updated American Geriatrics Society/British Geriatrics Society clinical practice guideline for prevention of falls in older persons. J Am Geriatr Soc. 2011; 59(1):148–57. doi: 10.1111/j.1532-5415.2010.03234.x 21226685

3. National Institute for Health and Care Excellence [Internet]. Falls in older people: assessing risk and prevention. Clinical guideline [CG161]; 2013. [Cited 2018 May 20]. Available from:

4. Bekibele CO, Gureje O. Fall incidence in a population of elderly persons in Nigeria. Gerontology. 2010; 56(3):278–83. doi: 10.1159/000236327 19738364

5. Doré AL, Golightly YM, Mercer VS, Shi XA, Renner JB, Jordan JM et al. Lower-extremity osteoarthritis and the risk of falls in a community-based longitudinal study of adults with and without osteoarthritis. Arthritis Care Res (Hoboken). 2015; 67(5):633–9.

6. Harada K, Shibata A, Oka K, Nakamura Y. Association of muscle-strengthening activity with knee and low back pain, falls, and health-related quality of life among Japanese older adults: a cross-sectional survey. J Aging Physical Act. 2015; 23(1):1–8.

7. Houry D, Florence C, Baldwin G, Stevens J, McClure R. The CDC Injury Center’s response to the growing public health problem of falls among older adults. Am J Lifestyle Med. 2016; 10(1).

8. Leveille SG, Jones RN, Kiely DK, Hausdorff JM, Shmerling RH, Guralnik JM, et al. Chronic musculoskeletal pain and the occurrence of falls in an older population. J Am Geriatr Soc. 2009; 302(20):2214–21.

9. Asai T, Misu S, Sawa R, Doi T, Yamada M. Multi-chronic musculoskeletal pain is a useful clinical index to predict the risk of falls in older adults with normal motor function. Aging Clin Exp Res. 2015; 27:711–6. doi: 10.1007/s40520-015-0340-5 25753186

10. Patel KV, Phelan EA, Leveille SG, Lamb SE, Missikpode C, Wallace RB, et al. High prevalence of falls, fear of falling, and impaired balance in older adults with pain in the United States: findings from the 2011 National Health and Aging Trends Study. J Am Geriatr Soc. 2014; 62(10):1844–52. doi: 10.1111/jgs.13072 25283473

11. Stubbs B, Eggermont L, Patchay S, Schofield P. Older adults with chronic musculoskeletal pain are at increased risk of recurrent falls and the brief pain inventory could help identify those most at risk. Geriatr Gerontol Int. 2015; 15(7):881–8. doi: 10.1111/ggi.12357 25163605

12. Hannan MT, Gagnon MM, Aneja J, Jones RN, Cupples LA, Lipsitz LA et al. Minimizing the tracking of falls in studies of older participants: comparison of quarterly telephone recall with monthly falls calendars in the MOBILIZE Boston Study. Am J Epidemiol. 2010; 171(9):1031–6. doi: 10.1093/aje/kwq024 20360242

13. Thomas E, Wilkie R, Peat G, Hill S, Dziedzic K, Croft P. The North Staffordshire Osteoarthritis Project—NorStOP: prospective, 3-year study of the epidemiology and management of clinical osteoarthritis in a general population of older adults. BMC Musculoskelet Disord. 2004; 5:2. doi: 10.1186/1471-2474-5-2 14718062

14. Benson T. The history of the Read Codes: the inaugural James Read Memorial Lecture 2011. Inform Prim Care. 2011; 19(3):173–82. doi: 10.14236/jhi.v19i3.811 22688227

15. NHS Digital [Internet]. Read Codes; 2018. [Cited 2018 Aug 8]. Available from:

16. NHS Digital [Internet]. Hospital Episode Statistics. About the HES database; 2019. [Cited 2019 May 2]. Available from:

17. Office For National Statistics. An Executive Summary, 2010-based NPP Reference Volume; 2012. [Cited 2019 Oct 10]. Available from

18. Lacey RJ, Lewis M, Jordan K, Jinks C, Sim J. Interrater reliability of scoring of pain drawings in a self-report health survey. Spine (Phila, Pa 1976). 2005; 30(16):E455–8.

19. McBeth J, Nicholl BI, Cordingley L, Davies KA, Macfarlane GJ. Chronic widespread pain predicts physical inactivity: Results from the prospective EPIFUND study. Eur J Pain. 2010; 14(9):972–979. doi: 10.1016/j.ejpain.2010.03.005 20400346

20. Wolfe F, Smythe HA, Yunus MB, Bennett RM, Bombardier C, Goldenberg DL, et al. The American College of Rheumatology 1990 Criteria for the Classification of Fibromyalgia: Report of the Multicenter Criteria Committee. Arthritis Rheum. 1990; 33(2):160–72. doi: 10.1002/art.1780330203 2306288

21. Welsh VK, Clarson LE, Mallen CD, McBeth J. Multisite pain and self-reported falls in older people: systematic review and meta-analysis. Arthritis Res Ther. 2019; 21(1):67. doi: 10.1186/s13075-019-1847-5 30795790

22. Office for National Statistics. Standard occupational classification 2000. Vol. 2. The coding index. London: The Stationery Office; 2000.

23. Office for National Statistics. The National Statistics Socio-economic classification user manual. Version 1, 1. London: The Stationery Office; 2002.

24. Muller S, Thomas E, Peat G. The effect of changes in lower limb pain on the progression of locomotor disability in middle and old age: evidence from the NorStOP cohort with 6-year follow up. Pain. 2012; 153(5):952–9. doi: 10.1016/j.pain.2011.12.006 22386475

25. GOV.UK [Internet]. Official Statistics: English indices of deprivation; 2018 [Cited 2018 Jun 30]. Available from:

26. Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987; 40(5):373–83. doi: 10.1016/0021-9681(87)90171-8 3558716

27. Khan NF, Perera R, Harper S, Rose PW. Adaptation and validation of the Charlson Index for Read/OXMIS coded databases. BMC Fam Pract. 2010; 11:1. doi: 10.1186/1471-2296-11-1 20051110

28. Austin SR, Wong YN, Uzzo RG, Beck JR, Egleston BL. Why summary Comorbidity Measures Such As the Charlson Comorbidity Index and Elixhauser Score Work. Med Care. 2015; 53(9):e65–72. doi: 10.1097/MLR.0b013e318297429c 23703645

29. World Health Organisation [Internet]. Body mass index–BMI; 2019/ [Cited 2019 Oct 2]. Available from:

30. Zigmond AS, Snaith RP. The Hospital Anxiety and Depression Scale. Acta Psychiatr Scand. 1983; 67(6):361–70. doi: 10.1111/j.1600-0447.1983.tb09716.x 6880820

31. Bjelland I, Dahl AA, Haug TT, Neckelmann D. The validity of the Hospital Anxiety and Depression Scale. An updated literature review. J Psychosom Res. 2002; 52(2):69–77. doi: 10.1016/s0022-3999(01)00296-3 11832252

32. Snaith RP. The Hospital Anxiety and Depression Scale. Health Qual Life Outcomes. 2003; 1:29. doi: 10.1186/1477-7525-1-29 12914662

33. Bergner M, Bobbit RA, Carter WB, Gilson BS. The Sickness Impact Profile: development and final revision of a health status measure. Med Care. 1981; 19:787–805. doi: 10.1097/00005650-198108000-00001 7278416

34. Westoby CJ, Mallen CD, Thomas E. Cognitive complaints in a general population of older adults: prevalence, association with pain and the influence of concurrent affective disorders. Eur J Pain. 2009; 13(9):970–6. doi: 10.1016/j.ejpain.2008.11.011 19110455

35. Langa KM, Levine DA. The diagnosis and management of mild cognitive impairment: a clinical review. JAMA. 2014; 312(23):2551–61. doi: 10.1001/jama.2014.13806 25514304

36. Joint Formulary Committee. British National Formulary: volume 65. Pharmaceutical Press; 2013.

37. Bedson J, Belcher J, Martino OI, Ndlovu M, Rathod T, Walters K et al. The effectiveness of national guidance in changing analgesic prescribing in primary care from 2002 to 2009: an observational database study. Eur J Pain.2013; 17(3):434–43. doi: 10.1002/j.1532-2149.2012.00189.x 22865816

38. Ware JE Jr, Sherbourne CD. The MOS 36-item short-form health survey (SF-36). I. Conceptual framework and item selection. Med Care. 1992; 30(6):473–83. 1593914

39. Bohannon RW, Brennan PJ, Pescatello LS, Marschke L, Hasson S, Murphy M. Using self-report and speed to screen for gait limitations. Phys Occup Ther Geriatr. 2005; 23:1–8.

40. Muller S, Thomas E, Peat G. Derivation and testing of an interval-level score for measuring locomotor disability in epidemiological studies of middle and old age. Qual Life Res. 2009; 18(10):1341–55. doi: 10.1007/s11136-009-9553-4 19911307

41. Merbitz C, Morris J, Grip JC. Ordinal scales and foundations of misinference. Arch Phys Med Rehabil. 989; 70(4):308–12. 2535599

42. Wright BD, Linacre JM. Observations are always ordinal; measurements, however, must be interval. Arch Phys Med Rehabil. 989; 70(12):857–60. 2818162

43. Welmer AK, Rizzuto D, Calderon-Larranaga A, Johnell K. Sex differences in the association between pain and injurious falls in older adults: a population-based longitudinal study. Am J Epidemiol. 2017; 186(9):1049–1056. doi: 10.1093/aje/kwx170 28535169

44. National Osteoporosis Guideline Group. Assessment of fracture risk; 2017. [Cited 2018 Jun 26]. Available from:

45. Cummings SR, Nevitt MC, Kidd S. Forgetting falls. The limited accuracy of recall of falls in the elderly. J Am Geriatr Soc. 1998; 36(7):613–6.

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