Prevalence and risk factors of falls among community-dwelling older people: results from three consecutive waves of the national health interview survey in Taiwan

Abstract

Background An aging society incurs great losses due to fall-related injuries and mortalities. The foreseeable increased burden of fall-related injury among older people requires a regular nationwide study on the fall epidemic and prevention strategies. Methods The fall epidemic was examined using data from three consecutive waves of the National Health Interview Survey (2005, 2009, and 2013). Common explanatory variables across these surveys included sociodemographic factors (age, sex, and difficulty in performing activities of daily living (ADL) or instrumental ADL), biological factors (vision, comorbidities, urinary incontinence, and depressive symptoms), and behavioral risk factors (sleeping pill use, and frequency of exercise). After the univariate and bivariate analyses, the prevalence of falls was investigated using multiple linear regression models adjusted for age group, sex, and year of survey. A multivariate logistic regression model for falls with adjustments for these common explanatory variables was established across three waves of surveys. The effect of fall prevention programs was examined with the effect size in terms of age-specific and sex-specific prevalence of falls and fall-related hospitalization rates during 2005 and 2009. Results For each survey, there were consecutively 2722; 2900; and 3200 respondents with a mean age of 75.1, 75.6, and 76.4 years, respectively. The multiple linear regression model yielded a negative association between the prevalence of falls and year of survey. Several sociodemographic and biological factors, including female sex, difficulty in performing one basic ADL, difficulty in performing two or more instrumental ADLs, unclear vision, comorbidities, urinary incontinence, and depressive symptoms, were significantly associated with falls. In contrast to the universal positive effect on the prevalence of falls among older adults, the effect size of fall-related hospitalization rates revealed a 2% relative risk reduction only for those aged 65–74 years, but deteriorated for those aged 75–84 (− 10.9%). Conclusion Although the decline in fall prevalence over time supports existing fall intervention strategies in Taiwan, the differential prevention effect and identification of risk factors in older people suggest the necessity of adjusting fall prevention programs.

Prevalence and Factors Associated with Falls among Older Outpatients

“…This result is similar to that of Subramanian et al conducted in Indian outpatients aged >60 years [ 29 ]. However, the reported global fall rates in community-dwelling older people vary from 4% to 35% [ 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 ], and the proportion of recurrent falls in our study is lower than those in the studies in developed countries [ 30 , 31 ]. These inconsistencies could be due to differences in culture, family structure and medical care conditions across countries.…”

The impact of urinary incontinence on falls: A systematic review and meta-analysis

“…Next, 1,177 studies were excluded during primary screening. After reviewing the texts of 107 articles, we excluded 73 studies, resulting in the inclusion of 34 articles [ 2 , 7 – 11 , 14 – 40 ]. In addition, we found four eligible studies from a previous review [ 41 ].…”

“…The main characteristics of the studies are summarized in Table 1 [ 2 , 7 – 11 , 14 – 40 , 42 – 46 ]. The meta-analysis revealed that, overall, 27.6% of participants (n = 63,618) experienced falls.…”

“…The definitions of falls varied across the reviewed studies. Twenty-nine studies defined a fall as ≥1 fall event [ 7 – 9 , 11 , 17 , 18 , 20 , 22 , 23 , 26 – 40 , 42 – 46 ], four studies defined a fall as ≥2 fall events [ 14 , 15 , 21 , 25 ], and five studies defined a fall as ≥1 fall event and recurrent falls as ≥2 fall events [ 2 , 10 , 16 , 19 , 24 ].…”

“…Among the 38 studies, 14 studies did not adjust for confounding factors and were classified as studies with a critical risk of bias [ 8 – 11 , 14 , 20 , 22 , 25 – 27 , 30 , 39 , 45 , 46 ]. Seventeen studies had a serious risk of bias since more than one critically important confounding factor, namely age, sex, and physical function, was not appropriately adjusted or UI was not properly defined [ 15 – 19 , 21 , 28 , 29 , 31 , 35 – 38 , 40 , 42 – 44 ]. Seven studies, which were appropriately adjusted for confounding factors, had a moderate risk of bias [ 2 , 7 , 23 , 24 , 32 – 34 ].…”