Accidents are the fifth-leading cause of death in adults aged 65 years or older (after cardiovascular diseases, cancer, stroke, and respiratory causes). Falls account for two-thirds of these accidental deaths. Falls are very common, with about 30% of community-dwelling older adults falling every year in developed countries. The incidence among institutionalized older people is even higher, with a mean percentage of residents who fall each year of over 40%.1 Most falls do not cause death, but 5%–10% of falls result in serious injuries such as head injuries or fractures.
Falls have a strong impact on health and quality of life of older people. In recent decades, several epidemiologic studies have investigated risk factors for falls. Although investigators have not used consistent classifications, risk factors for falls are generally categorized as intrinsic and extrinsic. Intrinsic factors are individual-specific and include advanced age, chronic disease, muscle weakness, gait and balance disorders, and cognitive impairment. Extrinsic factors generally include medication use, environmental hazards, and hazardous activities. Lord et al2 proposed a more analytic classification, dividing risk factors into sociodemographic factors, balance and mobility factors, sensory and neuromuscular factors, psychologic factors, medical factors, medication use, and environmental factors. Except for 2 meta-analyses on drugs3 and muscle weakness,4 previous reviews of risk factors for falls1,5–11 have not used standard meta-analytic techniques to summarize the evidence.
In 2003, the National Institute of Clinical Excellence9 provided guidelines for the prevention of falls in older persons. These guidelines included a systematic review of prospective cohort studies published from 1998 through 2002. The mean odds ratio (OR) and relative risk (RR) for 16 risk factors extracted from 28 studies were computed. Factors predictive of falling for community-dwelling older people included history of falling, gait deficit, balance deficit, mobility impairment, fear of falling, visual impairment, cognitive impairment, urinary incontinence, and home hazards. Since then, several new studies have been published. Our objective is to provide an updated comprehensive systematic review of prospective studies on risk factors for falls in community-dwelling older people.
Search Strategy and Selection Criteria
As the basis for our analysis, we used the systematic search of the relevant literature conducted in the review9 of studies from 1998 to 2002, and previous reviews.1,5–11 In addition to their search, we performed a MEDLINE search of the literature from 2002 to December 2008. Three search themes were combined using the Boolean operator “and.” The first theme, “falls,” combined in title/abstract fall or falls or falling or faller* or fallen or slip* or trip* or Medical Subject Heading (MeSH) accidental falls. The second theme, “elderly,” combined in title/abstract old or older or senior* or elder* or aged or geriatric* or middle?age*. The third theme, “risk,” combined in title/abstract risk* or assess* or predict* or history* or screen* or probabilit* or Medical Subject Heading (MeSH) risk. This search strategy was derived from the one applied by previous reviewers.9
Two investigators (S.D., E.N.) independently reviewed titles and abstracts, and selected articles addressing falls in the elderly. Disagreements were resolved by discussion and consensus. We considered articles published in English, Italian, French, Spanish, Portuguese, and German. On a second sift, we selected original studies on risk factors for fall with the following inclusion criteria:
- At least 80% of the sample aged 65 years or older.
- Prospective study design.
- Sample size greater than 200 subjects.
- At least 80% of subjects living in the community.
- Number of subjects experiencing one or more falls during follow-up as an outcome.
Additionally, the reference lists of the previous reviews were searched to identify studies that met the inclusion criteria and were published before 2002.
Data Extraction and Analysis
For each study included, the full text was retrieved and the following data were extracted: location, year of publication, size and mean age of the sample, outcome assessed, and method used to record falls.
We considered 2 outcomes:
- All fallers: persons who fell at least once during the follow-up.
- Recurrent fallers: persons who fell at least twice during the follow-up (within 6 months, or within 1 year, depending on the information given in the study).
The frequency of assessment was defined as follows:
- High: when the fall was recorded on a calendar or persons were interviewed at least every 3 months.
- Intermediate: when persons were interviewed less frequently than in (1) but at least every 6 months.
- Low: when persons were interviewed only once a year.
For each risk factor, we extracted the OR or RR, together with CIs, and details about the statistical methodology (eg, confounders considered, analytic method used). When the OR or the RR was not provided, we computed a crude OR if possible.
We followed the risk-factors classification proposed by Lord et al.2 Two investigators performed the extraction of the data in duplicate to avoid errors. Multivariate estimates were always selected when available, otherwise the unadjusted results were recorded. We pooled studies that presented ORs or RRs.
Given the high number of potential risk factors, we restricted our analysis to those for which an outcome was assessed by at least 5 studies. In some cases, the same risk factor was measured in different ways. For example, depression was diagnosed by 2 scales—the Center for Epidemiologic Studies Depression Scale (CES-D) and the Geriatric Depression Scale (GDS). Similarly, cognitive impairment was defined by a Mini Mental State Examination (MMSE) score <24 in some studies, and <18 in others. Because we did not have the original data, we used cutpoints given in the original studies. For body mass index, we used either <20 kg/m2 or <25 kg/m2 as the cutpoint, and for education we used the best proxy for a low grade (10, 11, or 12 years). However, when we judged that the measure used in a study was not comparable with ones used in other studies, we excluded that study when examining that risk factor.
Each outcome was analyzed separately. For dose–response analysis (ie, for age, number of drug prescriptions, etc) we used the method proposed by Greenland and Longnecker12 that estimates study-specific slopes from the natural logarithm of the RR or OR across exposure categories, assigning to each class the dose corresponding to the midpoint of the range.
We used RevMan, version 4.3.2, for Windows by the Cochrane Collaboration (http://www.cc-ims.net/revman) to analyze data. We estimated pooled ORs and 95% confidence intervals (CIs) using random-effects models.13 We assessed statistical heterogeneity among studies using the χ2 test. The following additional subgroup analyses were performed: studies presenting multivariate ORs versus unadjusted ORs; studies where the mean or median age of subjects was >75 years versus studies where the mean age was 75 years or younger; follow-up longer than 1 year versus shorter; and high frequency of fall assessment versus low frequency.
The MEDLINE search produced 4155 citations. Review of titles and abstracts resulted in the selection of 1447 papers, among which 356 were original studies, and 44 met the inclusion criteria. An additional 30 studies were identified from the references of previously published reviews.1,5–11 The flowchart of study selection is shown in the Figure. Selected characteristics of the 74 included articles14–87 are reported individually in Table 1 and summarized in Table 2. Most studies were conducted in the United States or Europe, with mean/median cohort age of 75 years or older, a sample size less than 500 (range: 211–9704), a duration of follow-up 1 year or less, and publication after 2000. A total of 31 risk factors were assessed by 5 or more studies in a comparable manner for at least 1 outcome.
Tables 3–6 provide the combined ORs and 95% CIs and heterogeneity test for each risk factor for 2 outcomes: all fallers and recurrent fallers. ORs are reported (1) for all studies, (2) only for studies reporting multivariate analysis, and (3) only for studies with a high frequency of fall assessment. eAppendix 1 (https://links.lww.com/EDE/A404) provides forest plots with results of individual studies, and eAppendix 2 (https://links.lww.com/EDE/A404) contains tables with other subgroup analyses.
Table 3 shows the results for sociodemographic factors. Advanced age and sex were the factors most frequently investigated. For a 5-year increase in age, the OR was 1.12 (95% CI = 1.07–1.17) for all fallers and 1.12 (1.07–1.18) for recurrent fallers. Individual studies were heterogeneous for both outcomes (P = <0.0001 and 0.009, respectively). Nonetheless, all studies showed a consistent rise in risk with age. Female sex was associated with an increased risk of falling (OR = 1.3 for all fallers and OR = 1.3 for recurrent fallers), and again the results from individual studies were heterogeneous (P = 0.004 and P = <0.0001, respectively). Most studies found an increased risk for women, both for all fallers and recurrent fallers. Risks for living alone were OR = 1.3 for all fallers and OR = 1.3 for recurrent fallers, history of falls (OR = 2.8; 3.5), physical disability (OR = 1.6; 2.4), disability in instrumental activities of daily life (OR = 1.5; 2.0), and use of a walking aid (OR = 2.2; 3.1). Physical activity reduction, low education, and low body mass index were not associated with the risk of falling.
Table 4 shows the effects of psychologic and medical factors. All the medical conditions investigated showed a positive association with both outcomes. The strongest associations were with vertigo, Parkinson disease, and fear of falling: for recurrent fallers the ORs were 2.3 (1.9–2.8) for vertigo, 2.8 (1.8–4.6) for Parkinson disease, and 2.5 (1.8–3.5) for fear of falling. Comorbidity and self-perceived health status were also associated with falls: an increment of 1 medical condition resulted in a pooled overall OR of 1.2 (1.2–1.3) for any faller and 1.4 (1.2–1.6) for recurrent fallers.
Table 5 shows the relation with medication use. Use of sedatives, antihypertensives, and, in particular, antiepileptics (OR = 1.9 all fallers and 2.7 for recurrent fallers) were directly associated with risk of falling, as was number of medications used (OR = 1.06 for both outcomes with 1 drug increase).
Table 6 shows the effects of mobility and sensory factors. The high heterogeneity in methods used to assess muscle weakness and balance impairment did not allow results from different studies to be combined. Gait problems increased the risk of falls, with an overall OR of 2.1 (1.8–2.3) for all fallers and 2.2 (1.5–3.2) for recurrent fallers. Vision and hearing impairment also increased risk, especially vision problems (1.4 for all fallers and 1.6 for recurrent fallers).
This meta-analysis of risk factors for falls found ORs around 2–3 for history of falls, vertigo, Parkinson disease, fear of falling, gait problems, use of walking aids, and use of antiepileptic drugs. For most other factors considered, ORs were less than 2. ORs were generally higher for recurrent fallers than for all fallers.
Although many studies have investigated risk factors for falls, a comprehensive and quantitative summary has been lacking. We included only studies with a prospective design to avoid problems of reverse causality, given that some factors (eg, fear of falling) are consequences as well as risk factors for falls. A prospective design ensures that the exposure was measured before the occurrence of the outcome. We excluded cohorts with fewer than 200 subjects to avoid studies based only on a small number of outcomes or very few exposed subjects.
Several of the studies presented crude ORs only. To investigate the role of possible confounders on the association between each factor and the risk of falling, we also calculated pooled ORs based on studies in which the OR was adjusted at least for age and sex, and other potential confounders when possible. In the 2003 review of risk factors,9 studies presenting adjusted ORs were given greater consideration. Given the strong possibility of confounding by age and sex, as well as by other correlated factors, adjusted ORs are clearly more reliable. The use of adequate statistical techniques is a further indicator of better quality of the study. However, it is also possible that in some studies a number of risk factors were investigated, and that the ones included in the multivariate analyses were only those significantly associated in the univariate ones. Considering only studies presenting adjusted ORs may thus lead to an overestimation of the overall OR. Moreover, in some instances, there were only 1 or 2 studies presenting multivariate results. In any case, the difference between the pooled estimate based on all individual ORs and the one based only on adjusted ORs was not substantial for most factors, although the pooled adjusted estimates tended to have wider confidence intervals, given that these were generally based on fewer studies. A notable exception was cognition impairment, for which multivariate ORs were higher than univariate ones for both outcomes.
Falls are often underreported, and particularly falls without injury.88 For this reason, we also estimated pooled ORs including only studies in which the fall event had been recorded on a fall calendar or ascertained with an interview at least every 3 months. This also can be considered as an indicator of better quality. Again, no major differences were observed for most factors when the analysis was restricted to studies with better outcome assessment.
When interpreting the results from this meta-analysis, one must consider the issue of heterogeneity among studies, which was substantial for some—but not all—factors. A higher heterogeneity leads to wider confidence intervals, since a random-effects model was used. For this reason, in evaluating the strength of the association of each factor with the risk of falling, one should consider the whole confidence interval of the summary OR, rather than the point estimate only. From the 31 risk factors considered, the P value of the heterogeneity test in the overall analysis was <0.10 in 23 cases for all fallers and in 19 cases for recurrent fallers. In most instances, however, results were fairly consistent in the direction of the effect (ie, pointing toward an increase or decrease in risk), even though studies differed in the estimation of the effect size. (See forest plots in eAppendix 1 [https://links.lww.com/EDE/A404]). The subgroup analyses in eAppendix 2 (https://links.lww.com/EDE/A404) explored the role of some characteristics of studies in explaining heterogeneous results. Other characteristics (eg, other design or population issues, including methodologic limitations and biases) may further explain differences in results.
Despite these potential limitations, some clear associations emerged from this analysis.
This review underscores the plethora of factors that affect the risk of falling, with a weak or moderate OR for most (generally below 2). Although most associations are not large, these factors are common in the older population, and often a person presents several factors, thus being at considerable risk of falling.
The estimated ORs were generally higher for “recurrent fallers” than for “all fallers,” indicating that the subjects who experience more than one fall are a distinct risk group. Although one fall may occur by chance alone, the repetition of the event suggests an underlying high-risk state.
Some nonspecific indicators of a high baseline risk (history of falls, fear of falling, and use of walking aids) were associated with about a 3-fold risk of falling. These factors cannot be prevented, but they may help identify persons at high risk of falling and thus likely to benefit most from preventive interventions.
Other factors showing ORs around 2 were dizziness and vertigo, gait problems, and antiepileptic drug use, plus cognition impairment when adjusted ORs only were considered. Prescriptions of newer antiepileptic drugs have been increasing in recent years in several countries, particularly for the treatment of pain.89 There is a need to explore the increased risk of falls by type of drug, given that falls may be an important adverse event that must be considered when deciding the treatment of pain in older people.
Several potentially relevant factors were not addressed in this study, either because they were considered by too few studies (eg, anemia, hypovitaminosis D, use of antidepressants, antipsychotics or insulin, footwear, use of bifocal lenses) or because the risk factor was measured in noncomparable ways (eg, muscle weakness, balance impairment, environmental hazards). For the first group of factors, there is a need for further studies to explore these associations. In the second group, there is a need for consensus on measures to evaluate the factor, to improve comparability among studies. For example, the Prevention of Falls Network Europe identified over 30 different measures of balance within the European Union (http://www.profane.eu.org/eu_map/index.php). The same problem was raised by a recent review on exercise for improving balance in older people performed within the framework of the Cochrane Collaboration.90 The authors recommended “a consensus of outcome measures for evaluating the effects of interventions of balance ability” and, we add, for the evaluation of balance ability in older people in general. With regard to muscle weakness, some studies measured upper-limb muscle strength and others lower-limb strength, using different methods, with none of the measures used in at least 5 studies.
This meta-analysis provides the first comprehensive evidence-based assessment of risk factors in community-dwelling older people. It shows the need for improved quality in reporting studies on risk factors in older people, as well as for further research on potentially important neglected factors, and for improvements in comparability of risk-factor measurement.
We thank Ivana Garimoldi for her editorial assistance.
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