Fall risk factors for individuals under the age of 65 years with type 2 diabetes mellitus

Abstract

Introduction

The purpose of this study was to examine self-reported falls and fall risk factors in people with type 2 diabetes mellitus aged under 65 years.

Methods

This study was a cross-sectional analysis of 64 participants at a primary care facility in the western United States of America. The following fall risk factors were examined for differences between groups (fallers vs. non-fallers): age, body mass index, depression, fear of falling, neuropathy, number of medications, sedentary behavior, and visual co-morbidities. Multivariate logistic regression was used to determine relationships with self-reported falls (yes/no recent fall as defined by the participant).

Results

Forty-five percent of participants reported a recent fall. The following fall risk factors produced significant differences between fallers and non-fallers: depression scores (p = .01), fear of falling (p < .01), and number of medications currently being taken (p = .04). Through multivariate logistic regression, the fear of falling score (p < .01) was the only significant relationship with self-reported falls in the model that included age, body mass index, depression, fear of falling, neuropathy, number of medications, sedentary behavior, and visual co-morbidities.

Conclusion

Psychological fall risk factors such as fear of falling are factors that should be considered early on in a diagnosis of type 2 diabetes mellitus because they may have an effect on falls, as evidenced in this sample of adults with type 2 diabetes mellitus aged under 65 years.

Keywords

Fall risk factors fall risk type 2 diabetes mellitus fear of falling occupational therapy

Introduction

Worldwide there are at least 422 million people diagnosed with diabetes, and that number is growing (World Health Organization (WHO), 2016). Type 2 diabetes mellitus (T2DM), which is a chronic condition characterized by the body’s inability to correctly produce or process insulin, leading to abnormal blood glucose levels, is the most common form of diabetes. Given that more people are experiencing T2DM, increased attention should be paid to understanding the disease as well as the cascading effects of T2DM. T2DM is a systemic disease that frequently results in structural and functional changes of multiple body systems: cardiovascular, digestive, musculoskeletal, ocular, and urinary systems (Ruof et al., 2004). Medical complications resulting from changes in these body systems are often considered with a diagnosis of T2DM. Less often considered are complications related to participation in everyday life that occur as a result of T2DM. Falls associated with diabetes are an example of one complication that could greatly impact quality of life, secondary to potential injury (Gravesande and Richardson, 2017) or fear avoidance of meaningful activities (Delbaere et al., 2004).

The diagnosis of diabetes is an independent fall risk factor, and physiological, psychological, and behavioral complications are also associated with increased fall risk in those with diabetes (Roman de Mettelinge et al., 2013). Physiologically, diabetes-related visual co-morbidities, lower extremity somatosensory changes, and being overweight are fall risk factors for individuals with T2DM (Gravesande and Richardson, 2017). Visual co-morbidities and lower extremity sensory changes can occur when diabetes is poorly controlled and the lack of control results in damaged blood vessels or peripheral nerves (WHO, 2016). For example, decreased perfusion to the blood vessels supplying the retina can cause diabetic retinopathy, resulting in visual changes and potential vision loss. Vision loss can cause a myriad of other related fall risks such as decreased balance, impaired postural control, and difficulty seeing environmental hazards (Horak, 2006; Reed-Jones et al., 2013). Similarly, nerve damage from diabetes can lead to somatosensory changes. Compared to individuals without diabetes, those with diabetic peripheral neuropathy were 20 times more likely to fall (Richardson and Ashton-Miller, 1996), potentially because diabetic peripheral neuropathy makes it more difficult for an individual to be aware of foot placement. Additionally, in a systematic review of fall risk factors for older adults with T2DM, body mass index (BMI) ≥25 kg/m² was cited as a fall risk factor in this population, and BMI ≥30 kg/m² with other co-morbidities was cited as a risk factor for multiple falls (Gravesande and Richardson, 2017).

Adults with T2DM also experience psychological co-morbidities, such as increased depression and fear of falling (FoF), that contribute to higher fall risk. In a cross-sectional study of individuals with diabetes, 22% reported depression as measured by the Hospital Anxiety and Depression Scale (HADS) (Collins et al., 2009). In the general older adult population, depression was associated with a 32% increase in fall risk (Lawlor et al., 2003). For people less than 65 years old with T2DM, there is currently no research connecting co-morbid depression to fall risk. Additionally, when compared to healthy controls, individuals with T2DM reported other psychological fall risk factors, such as significantly higher FoF (Reeves et al., 2017), which is strongly associated with increased fall risk (Friedman et al., 2002). For individuals with T2DM, higher FoF is associated with higher activity restrictions, and thus fall rates were not significantly different between matched pairs of individuals with and without normal glycemic readings (Bruce et al., 2015).

In addition to physiological and psychological factors, behavioral factors related to diabetes could also be associated with increased fall risk, for example limited engagement in physical activity. Fallers are generally more sedentary than those who do not experience falls (National Center for Injury Prevention and Control (NCIPC), 2015), and fallers may limit their daily activity participation due to fear avoidance (Delbaere et al., 2004). Individuals with T2DM are likely more sedentary than their peers, with 41% of adults with diabetes self-reporting being physically inactive (CDC, 2017), and this sedentary behavior could ultimately lead to increased falls due to general deconditioning and an unhealthy cycle of continued decreased activity and participation. Lastly, polypharmacy is a common behavioral fall risk factor (Pfortmueller et al., 2014), with the interaction of medications leading to complications that may cause falls (NCIPC, 2015). For people with diabetes, fall risk increased when they were taking four or more prescription medications (Huang et al., 2010). Diabetes-related medication (that is, glucose-lowering medications) did not increase fall risk; however, other medications that could be prescribed for co-morbidities (for example psychotropic medications) could increase fall risk further (Park et al., 2015).

Though there exists a large body of research examining the relationships among fall risk factors and T2DM, a major shortcoming of this research is the primary focus on older adults (65+ years) (Chiba et al., 2015; Gravesande and Richardson, 2017; Vinik et al., 2015). The average age for diagnosis of T2DM is now 54 years old (Centers for Disease Control and Prevention, 2017), and T2DM has been shown to be an independent predictor of fall risk in older adults (Roman de Mettelinge et al., 2013), but we hypothesize that adults with T2DM younger than 65 years are also at high risk to fall. However, the risk factors that contribute to falls may be different for adults younger than 65 years. Although advanced age has repeatedly been shown to be an important risk factor for falls (Centers for Disease Control and Prevention, 2015; WHO, 2007), adults under the age of 65 years with chronic conditions like T2DM may have the same complications and co-morbidities as older adults with T2DM and could therefore be at a high risk of falling. A comprehensive understanding of the specific risk factors that contribute to fall rates among this younger population will begin to identify potential targets for intervention for occupational therapists and other health professionals. The purpose of this study was to examine which fall risk factors associated with self-reported falls in a sample of adults with T2DM less than 65 years old.

Methods

This was a cross-sectional study, and within these analyses only participants less than 65 years old were considered. Participants were recruited through convenience sampling from a safety-net primary care (PC) facility. Safety-net PC facilities provide care to uninsured or underinsured individuals who otherwise may not have access to care. PC providers referred participants, and flyers were put up in the clinic. For inclusion in this study, participants met the following criteria: a diagnosis of T2DM; ≥18 years and < 65 years old; and received services at the PC facility. Participants were excluded from the study if they met any of the following criteria (as assessed by the researchers’ clinical judgment at intake): reading level below 6th grade; inability to understand written or verbal instructions. All study procedures were approved by the local Institutional Review Board and all participants provided written informed consent. Participants completed written questionnaires containing items related to demographics, general health, and T2DM information. An occupational therapist or occupational therapy research assistant was available to answer questions or provide prompts.

Measures

The cross-sectional design included questions and assessments related to self-reported falls and fall risk factors. Items in these analyses integrated self-report of recent falls and possible fall risk factors based on recent literature and clinical judgment including: age (Ambrose et al., 2013); depression (Chiba et al., 2015); FoF (Bruce et al., 2015); neuropathy (NCIPC, 2015); number of medications; sedentary behavior; and visual co-morbidities. Recent falls were assessed with the question: “have you recently fallen?” Participants selected “yes,” “no,” or “do not remember.” The timeframe was then quantified by asking, “how often?” Participants then had the option to select “daily,” “weekly,” “monthly,” or “just once.” For the purposes of this paper, recent falls were considered based on the initial yes or no report in which participants individually determined what “recently fallen” meant for each of them. Fall recall is often unreliable after 1 month and individuals have difficulty remembering specific time frames (for example 3 to 6 months) (Ganz et al., 2005).

Physiological risk factors

Age was included as a fall risk factor because age is frequently cited in fall risk literature as a predictor of fall rates or future falls (Ambrose et al., 2013). Body mass index was calculated using height and weight and this standard formula: 703*weight (pounds)/[height (inches)]². Neuropathy was measured by the presence (yes) or absence (no) of neuropathy in the self-reported health history. Visual co-morbidities were measured as the presence (yes) or absence (no) of any of the following self-reported eye diseases: retinopathy, glaucoma, cataracts, or other.

Psychological risk factors

Depression was assessed using the 14-item self-report HADS (Whelan-Goodinson et al., 2009). Scores on the depression subscale range from 0–21, with higher scores indicating more severe depression. In PC populations, the HADS is a comprehensive screening tool for anxiety and depression, with good internal consistency (Bjelland et al., 2002). The Falls Efficacy Scale – International (FES-I) was used to examine FoF. The FES-I includes additional items related to self-ratings in the social domain of falling, and demonstrated good test–retest and internal reliability compared to other FoF assessments (Yardley et al., 2005). The FES-I is considered a reliable FoF measure.

Behavioral risk factors

The number of medications each participant was currently taking was self-reported. If individuals were unaware of their current number of medications, a medical chart review was completed. To determine the activity level and sedentary behavior of each participant, we used the International Physical Activity Questionnaire short form (IPAQ-SF). The IPAQ-SF is a seven-item self-report of activity level developed for use with adults (Lee et al., 2011). For these analyses we were specifically interested in the final question, which asked, “during the last 7 days, how much time did you usually spend sitting on a weekday?”

Data analysis

Data were analyzed using the Statistical Package for Social Sciences version 24 (IBM Corporation, 2017). We used mean and standard deviation to explain the demographic and fall risk factor characteristics of this sample. Demographic data and fall risk factors were compared between recent fallers and non-fallers. Chi-squared tests were used to determine differences between fallers and non-fallers regarding the following outcomes: gender; ethnicity; race; neuropathy; and visual co-morbidities. A Shapiro–Wilk test was used to assess for the normality of each variable. Mann–Whitney tests were used to examine the following fall risk factors: age; the depression subscale of the HADS scores; FES-I scores; number of medications; and IPAQ sitting hours. A multivariate logistic regression was completed to determine which fall risk factors were associated with a self-reported recent fall (yes/no). The multivariate logistic regression model included all of the identified fall risk factors of interest as independent variables: age in years; depression total score on the HADS; FES-I score; neuropathy self-report; number of medications; sedentary behavior as measured by the IPAQ-SF sitting hours per weekday; and visual co-morbidities as measured by self-reported eye diseases.

Results

Sixty-four participants were less than 65 years old and were included in the analyses. In response to the question “have you fallen recently?” 29 (45%) people reported “yes,” 35 (55%) people reported “no,” and zero participants selected “do not remember.” In the follow-up fall question, two participants reported daily falls, seven reported weekly falls, four reported monthly falls, 15 reported falling just once, and one person did not respond. The mean age of participants in the study was 52.45 ± 7.52 years. There were no significant differences seen between groups (self-reported fallers vs. non-fallers) for age, gender, ethnicity, or race (see Table 1).

Table 1.

Demographics and comparison between people with and without a self-reported recent fall.

Outcome measure (mean ± standard deviation)	Total (n = 64)	Recent fall (n = 29)	No recent fall (n = 35)	p-value
Age^b	52.45 (± 7.52)	52.11 (± 8.11)	52.86 (± 6.87)	.80
Gender (women)^a	31 (48%)	17 (59%)	14 (40%)	.14
Ethnicity (non-Hispanic/Latino)^a	43 (67%)	20 (69%)	23 (66%)	.78
Race (white)^a	53 (82.8%)	22 (76%)	31 (89%)	.18
Body mass index^b	34.29 (± 8.37)	33.25 (± 8.28)	35.16 (± 8.47)	.56
Depression subscale of the Hospital Anxiety and Depression Scale^b	6.28 (± 3.65)	7.62 (± 4.01)	5.17 (± 2.94)	.01*
Falls Efficacy Scale – International^b	28.97 (± 11.84)	35.93 (± 13.16)	23.20 (± 6.45)	<.01*
Neuropathy^a	36 (56%)	19 (66%)	17 (49%)	.17
Number of medications^b	9.08 (± 5.29)	10.55 (± 5.75)	7.86 (± 4.60)	.04*
International Physical Activity Questionnaire – Sitting (hours/weekday)^b	7.28 (± 5.40)	7.80 (± 6.07)	6.86 (± 4.84)	.58
Visual co-morbidities (cataracts, glaucoma, retinopathy, or other)^a	13 (20%)	8 (28%)	5 (14%)	.19

*significant at p<.05

^aChi-squared test

^bMann–Whitney U test

Four of the fall risk factors that were considered yielded significant differences between self-reported fallers vs non-fallers. Regarding psychological risk factors, fallers had significantly higher depression scores on the HADS depression subscale (p = .01, $η^{2} = . 10$ ). Additionally, fallers reported a significantly higher fear of falling according to the FES-I scores (p < .01, $η^{2} = . 28$ ), although both groups were above the cut-off (FES-I score of 23) indicating high fear of falling (Delbaere et al., 2010). Finally, fallers were taking significantly more medication than non-fallers: on average, fallers were taking about three more medications than non-fallers (p = .04, $η^{2} = . 07$ ). See Table 1 for additional between-group comparisons of fall risk factor outcomes. Regarding behavioral fall risk factors, fallers reported sitting for an hour more during a typical weekday than non-fallers, although this difference was not statistically significant (p = .58).

In the multivariate logistic regression model, FES-I was maintained in the model using backward stepwise selection. Only the FES-I score had a significant relationship with self-reported falls: for every one-point increase in FES-I score, individuals were 1.13 times more likely to have reported a fall (p<.01) (see Table 2).

Table 2.

Final multivariate logistic regression model for younger than 65 years old.

Independent variable	B	S.E.	P-value	Exp(B)	95% Confidence Interval for Exp(B)
Falls Efficacy Scale – International	.13	.04	<.01	1.13	1.06–1.21

Discussion

In this study, 45% of individuals with T2DM under 65 years old reported a recent fall, which was surprising as the average age was only 52 years. This prevalence of reported falls is much higher than expected because the rate is even higher than expected in adults older than 65, who report a 22% annual fall rate (Stevens et al., 2014). Comparatively, in a study that utilized the National Health Interview Survey to approximate fall rates for all adults, only 11.4% of middle-aged (45–64 years) adults reported a fall in the last year (Verma et al., 2016). The fall frequency in this study was much greater than fall estimations seen for other individuals in a similar age range, which indicates the need for further exploration of fall risk factors related to diabetes and the development of treatment interventions to manage fall risk factors within this younger, yet still vulnerable, population. Though several studies have examined fall rates for individuals with T2DM, the majority of these studies focused on older adults and elderly individuals (Chiba et al., 2015; Gravesande and Richardson, 2017; Vinik et al., 2015). When further examining fall risk factors in this sample of individuals younger than 65 years old, fallers had significantly higher depression scores and FES-I scores, and were using more medications, as compared to non-fallers. Additionally, higher FES-I scores were significantly associated with a self-reported recent fall, with higher FoF increasing the likelihood of a self-reported fall.

As seen in this study, psychological fall risk factors could potentially impact falls for individuals with T2DM. For example, the relationship between FoF and self-reported falls was significant in this sample. A study by Delbaere et al. (2010) revealed that FES-I scores greater than 23 indicated a high concern regarding falls. Participants in this study had particularly high FoF scores, with average FES-I scores of 29 overall and 36 for self-reported fallers. In a comparison of adults with T2DM to age-matched normoglycemic peers, the T2DM group had significantly higher FoF scores (Bruce et al., 2015). Despite these differences, Bruce and colleagues reported that fall rates were similar between the matched cohorts. They speculated that fall rates were equalized between groups because individuals with T2DM reported high FoF along with a nearly three times higher indoor activity restriction. Potentially, in a sample of individuals under 65 years, fall reports are still high despite a high FoF because individuals are still engaging in activity. Perhaps individuals would benefit from education to retain meaningful activity while reducing FoF so that they do not experience participation restrictions as they age. FoF is an important fall risk factor to consider for younger individuals with T2DM to prevent the potential of future activity limitations and participation restrictions.

In a systematic review that examined nonpharmacological fall risk factors for older adults with diabetes, physical and somatosensory factors had the greatest impact on individuals’ risk of falling (Gravesande and Richardson, 2017). Researchers cited the following primary fall risk factors for older adults with T2DM: “lower extremity pain, being overweight, and having one or more co-morbid conditions” (Gravesande and Richardson, 2017: 1462). In this sample of individuals aged under 65 years, FoF was the only independent variable that remained in the model and had a significant relationship with self-reported falls in a model that contained the following variables: age, BMI, depression, fear of falling, neuropathy, number of medications, sitting hours, and visual co-morbidities. Although proactive changes may need to take place regarding physical factors and falls, psychological factors may be a better therapeutic intervention area for adults with T2DM aged under 65 years. Addressing FoF as part of occupational therapy intervention could help to maintain participation and prevent activity limitations.

Some potential fall risk factors were not collected in this study, and therefore there may be other factors that are significantly related to self-reported falls that were not included in the data analysis. For example, these measures did not include a report of medication types, and therefore medications known to specifically increase the risk of falls could not be explored further. Additionally, there was no performance-based balance assessment included, but in future studies a performance-based balance measure should be considered in order to objectively assess balance as a fall risk factor. Also, no data were collected on the date of T2DM diagnosis or time since diagnosis. Therefore, some younger participants may have been diagnosed for a number of years and already be experiencing some co-morbidities. Self-reported falls were also classified as “recent” based on the participant’s individual perception of what recent means. In other studies participants had difficulty discerning between specific recall periods (Ganz et al., 2005). Therefore, participants were permitted to determine when a recent fall had occurred or not.

Regarding design, the sample included individuals from one PC safety-net clinic, which was largely comprised of individuals with low socioeconomic status (SES). Potentially, this sample had health inequalities associated with low SES that could have influenced the self-reporting of falls such that the results cannot be generalized to individuals in other SES brackets. The study was also a cross-sectional design and therefore the directionality of results cannot be verified. FoF may contribute to falls, but falls also may contribute to FoF. However, fear of falling is noted in both older adults who have fallen, and those who have never fallen (Friedman et al., 2002). In the current study, even the group who had not recently fallen reported high FoF scores (Delbaere et al., 2010). Therefore, it is important to consider that in this population there is a relationship between self-reported falls and FoF, although it is difficult to determine the directionality of the relationship with a cross-sectional design.

Implications for occupational therapy practice

Exploring fall risk factors as they relate to younger individuals with T2DM is important to consider because this population has a high percentage of self-reported falls that may impact quality of life and participation in meaningful activities. Occupational therapists should explore the role of psychological fall risk factors in preventative care for T2DM and interventions to best address these important fall risk factors for individuals with T2DM of all ages. Occupational therapy interventions should, in part, address FoF upon diagnosis of T2DM regardless of age to create fall management programs for this high-risk population.

Key findings

In a sample of adults younger than 65 years with T2DM, 45% self-reported a recent fall.

Fear of falling is an important clinical outcome to consider for adults with T2DM aged under 65 years.

What the study has added

Adults with T2DM younger than 65 years are also at risk of falling, and fear of falling is an important risk factor for falls to consider in this younger sample.

Footnotes

Research ethics

Ethical approval was obtained from the Colorado State University Institutional Review Board #15-6245H, January 26, 2016.

Consent

All participants provided written informed consent prior to participating in the study.

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and publication of this article.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was funded through the Program of Research & Scholarly Excellence mini-grant, Department of Occupational Therapy, Colorado State University.

Contributorship

Tara Klinedinst and Matthew Malcolm applied for ethical approval and contributed to the development of the project and data. All authors contributed to the methodology of this manuscript and the statistical analysis plan. Laura Swink carried out the statistical analysis plan and all authors assisted in interpretation of the data. Laura Swink wrote the draft of the manuscript, with input and edits from all authors throughout the process. All authors reviewed and edited the manuscript and approved the final version.

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