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Epidemiological survey of the feasibility of broadband ultrasound attenuation measured using calcaneal quantitative ultrasound to predict the incidence of falls in the middle aged and elderly
  1. Ling-Chun Ou1,2,3,
  2. Yin-Fan Chang4,
  3. Chin-Sung Chang4,
  4. Ching-Ju Chiu5,
  5. Ting-Hsing Chao6,
  6. Zih-Jie Sun4,
  7. Ruey-Mo Lin7,
  8. Chih-Hsing Wu4,5,8
  1. 1Department of Family Medicine, Antai Medical Cooperation, Tien Sheng Memorial Hospital, Pingtung, Taiwan
  2. 2Department of Nursing, Meiho University, Pingtung, Taiwan
  3. 3College of Education, National Kaohsiung Normal University, Kaohsiung, Taiwan
  4. 4Departments of Family Medicine, National Cheng Kung University Hospital, Tainan, Taiwan
  5. 5Institutes of Gerontology, National Cheng Kung University College of Medicine, Tainan, Taiwan
  6. 6Departments of Internal Medicine, National Cheng Kung University Hospital, Tainan, Taiwan
  7. 7Department of Orthopedics, Tainan Municipal An-Nan Hospital of China Medical University, Tainan, Taiwan
  8. 8Institutes of Behavioral Medicine, National Cheng Kung University College of Medicine, Tainan, Taiwan
  1. Correspondence to Dr Chih-Hsing Wu; paulo{at}mail.ncku.edu.tw

Abstract

Objectives We investigated whether calcaneal quantitative ultrasound (QUS-C) is a feasible tool for predicting the incidence of falls.

Design Prospective epidemiological cohort study.

Setting Community-dwelling people sampled in central western Taiwan.

Participants A cohort of community-dwelling people who were ≥40 years old (men: 524; women: 676) in 2009–2010. Follow-up questionnaires were completed by 186 men and 257 women in 2012.

Methods Structured questionnaires and broadband ultrasound attenuation (BUA) data were obtained in 2009–2010 using QUS-C, and follow-up surveys were done in a telephone interview in 2012. Using a binary logistic regression model, the risk factors associated with a new fall during follow-up were analysed with all significant variables from the bivariate comparisons and theoretically important variables.

Primary outcome measures The incidence of falls was determined when the first new fall occurred during the follow-up period. The mean follow-up time was 2.83 years.

Results The total incidence of falls was 28.0 per 1000 person-years for the ≥40 year old group (all participants), 23.3 per 1000 person-years for the 40–70 year old group, and 45.6 per 1000 person-years for the ≥70 year old group. Using multiple logistic regression models, the independent factors were current smoking, living alone, psychiatric drug usage and lower BUA (OR 0.93; 95% CI 0.88 to 0.99, p<0.05) in the ≥70 year old group.

Conclusions The incidence of falls was highest in the ≥70 year old group. Using QUS-C-derived BUA is feasible for predicting the incidence of falls in community-dwelling elderly people aged ≥70 years.

  • Falls
  • calcaneal quantitative ultrasound
  • smoking
  • incidence
  • living alone

This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/

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Footnotes

  • Contributors L-CO wrote the paper. C-HW wrote and revised the paper. L-CO and C-HW had the idea for the study and were involved in all aspects of this study. L-CO recruited the study participants. Y-FC, J-CC and C-SC helped interpret the data and made statistical suggestions. Z-JS, C-HW, T-HC and R-ML coordinated the study affairs and budget. All authors reviewed and approved the final version of this manuscript.

  • Funding National Cheng Kung University Hospital (NCKUH) (grant number: NCKUH-10102043).

  • Competing interests None declared.

  • Patient consent Obtained.

  • Ethics approval Institute Review Board of National Cheng Kung University Hospital (A-ER-100-347).

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data sharing statement Extra data can be accessed via the Dryad data repository at http://datadryad.org/ with the doi:10.5061/dryad.17tp1.

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