Letter submitted 5 May 2017 regarding Age and Ageing paper https://doi.org/10.1093/ageing/afw254 Dear Sir, Magota et al.  recently reported in this journal temporal patterning of 464 recorded falls by inpatients of a secondary emergency medical facility. Fall rate was higher during the night than day, particularly between October and February, the months of longest nighttime darkness, with greatest fall rate around dawn in association with morning bathroom activities. Hospital falls are a major challenge, because they reduce patient quality of life, in part due to loss of autonomy and independence, and increase morbidity and consequentially length of stay and health expenditures . Falls are the outcome of complex interactions between identified intrinsic (biological and behavioural) and extrinsic (socioeconomic and environmental) risk factors. Some of these are modifiable, e.g. lifestyle and housing design, maintenance, and lighting, and some are not, e.g. age, chronic medical conditions and medication adverse effects . Effective intervention programs, even when addressing only a single risk factor, can reduce fall occurrence and associated injury . The variable of fall occurrence time is ignored in most investigations of causality. This information is important because it enables exploration of temporal relationships of such events with scheduled inpatient activities according to intrinsic and extrinsic risk criteria and also clock-time and shift schedule-dependent patterns of fatigue, oversight and staffing of healthcare personnel [5–7]. We [6–8] previously reported prominent time-of-day, day-of-week and month-of-year variation in fall occurrence using time series study methods and analyses . One of these  involved five Italian non-university hospitals in which a fall prevention program had been initiated. It revealed 24-h (main peak at ~05:30 h) and seasonal patterns (main peak March–April) in elderly falls. Categorisation of the clock time of events according to the assessed intrinsic and extrinsic risk factors resulted in more precise understanding of their epidemiology and ultimately improvement of the instituted prevention program, e.g. based on knowledge bathroom falls are most frequent at ~06:30 h, hospital corridor falls are most frequent at ~11:450 h, and falls from bed due to failure of staff to position bedrails are most frequent at ~01:45 h as opposed to falls from bed with proper staff-positioned bedrails that are most frequent at ~05:30 h—around wake-up time . Although the design and investigative methods of the Magota et al.  and our  study differed, the time-of-day pattern of falls is similar; falls were greatest at dawn in association with wake-up bathroom toileting and hygienic activities. Nonetheless, further studies employing a time series approach are required to better understand the role during the 24 h of patient intrinsic and residential extrinsic fall risk factors, staffing number, schedule of routine duties—bedsheet changes and patient bathing, meal positioning, between-unit transfers, etc—and fatigue/sleepiness, attention, and cognitive functioning . Conflicts of interest None declared. References 1 Magota C, Sawatari H, Ando SI et al. . Seasonal ambient changes influence inpatient falls. Age Ageing 2017 Jan 4; doi: 10.1093/ageing/afw254 [Epub ahead of print]. 2 Deandrea S, Bravi F, Turati F, Lucenteforte E, La Vecchia C, Negri E. Risk factors for falls in older people in nursing homes and hospitals. A systematic review and meta-analysis. Arch Gerontol Geriatr 2013; 56( 3): 407– 15. Google Scholar CrossRef Search ADS PubMed 3 American Geriatrics Society, British Geriatrics Society, Prevention. AAoOSPoF. Guideline for the prevention of falls in older persons. American Geriatrics Society, British Geriatrics Society, and American Academy of Orthopaedic Surgeons Panel on Falls Prevention. J Am Geriatr Soc 2001; 49( 5): 664– 72. CrossRef Search ADS PubMed 4 Cameron ID, Gillespie LD, Robertson MC et al. . Interventions for preventing falls in older people in care facilities and hospitals. Cochrane Database Syst Rev 2012; 12: Cd005465. Google Scholar PubMed 5 Reinberg A, Smolensky MH, Riedel M et al. . Chronobiologic perspectives of black time–Accident risk is greatest at night: An opinion paper. Chronobiol Int 2015; 32( 7): 1005– 18. Google Scholar PubMed 6 Lopez-Soto PJ, Manfredini R, Smolensky MH, Rodriguez-Borrego MA. 24-hour pattern of falls in hospitalized and long-term care institutionalized elderly persons: a systematic review of the published literature. Chronobiol Int 2015; 32( 4): 548– 56. Google Scholar CrossRef Search ADS PubMed 7 Lopez-Soto PJ, Smolensky MH, Sackett-Lundeen LL et al. . Temporal patterns of in-hospital falls of elderly patients. Nurs Res 2016; 65( 6): 435– 45. Google Scholar CrossRef Search ADS PubMed 8 Manfredini R, Volpato S, Gallerani M et al. . When hospital patients fall: preliminary data from Ferrara, Italy. J Am Geriatr Soc 2011; 59( 6): 1144– 6. Google Scholar CrossRef Search ADS PubMed 9 Nelson W, Tong YL, Lee JK, Halberg F. Methods for cosinor-rhythmometry. Chronobiologia 1979; 6( 4): 305– 23. Google Scholar PubMed © The Author 2017. Published by Oxford University Press on behalf of the British Geriatrics Society.All rights reserved. For permissions, please email: firstname.lastname@example.org
Age and Ageing – Oxford University Press
Published: Sep 8, 2017
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