Abstract
Falls impose substantial health and economic burdens on older adults. Over half of falls in older adults occur at home, with many involving bathroom areas. Limited information is available on the presence of bathroom modifications for those who experience them. Therefore, we examined factors associated with bathroom modifications among older adults with at least one fall in the United States. We analysed the nationally representative 2016 Medicare Current Beneficiary Survey Public Use File of Medicare beneficiaries aged ≥65 years with ≥1 fall (n = 2,404). A survey-weighted logistic model was used to examine associations between bathroom modifications and factors including socio-demographic characteristics, health-related conditions, and fear of falling. Among Medicare beneficiaries with ≥1 fall, 55.5% had bathroom modifications and 50.1% had repeated falls (≥2 falls). Approximately 40.2% of those with repeated falls had no bathroom modifications. In the adjusted model, non-Hispanic Blacks (odds ratio [OR] = 0.38; p < 0.001) and Hispanics (OR = 0.64; p = 0.039) had lower odds of having bathroom modifications than non-Hispanic Whites. Fear of falling and activities of daily living limitations had incremental impacts on having bathroom modifications. This study highlights the need to improve disparities in bathroom modifications for non-Hispanic Black and Hispanic Medicare beneficiaries, including those with repeated falls. With the aging population and growing number of older minorities in the United States, reducing these disparities is vital for fall prevention efforts and aging-in-place.
Keywords: aging-in-place, bathroom modifications, disparities, falls, fear of falling, Medicare beneficiaries, repeated falls
1 |. INTRODUCTION
Falls in older adults are a common and serious public health problem. Statistics released by the Centers for Disease Control and Prevention (CDC) show that around one-third of adults aged 65 or older fall each year (Moreland et al., 2020). Having a fall doubles an individual’s risk of having another fall (Vieira et al., 2016). In 2018, approximately 32,000 deaths among older adults were related to falls, and over 950,000 older adults were hospitalised for fall injury treatments (Moreland et al., 2020). Falls in older adults impose a huge economic burden on the U.S. healthcare system. Total associated medical costs was estimated to be $50 billion in 2015 (Florence et al., 2018), with Medicare payments totalling $28.0 billion for nonfatal-related falls; $8.7 billion from Medicaid; and $12.0 billion from private and other payer spending (Florence et al., 2018).
As the main healthcare insurance provider in the United States, Medicare provided healthcare coverage for over 49 million beneficiaries aged 65 or older in 2017 (Centers for Medicare and Medicaid Services, 2020). By 2030, it is estimated that the total number of beneficiaries would reach 79 million (Umans & Nonnemaker, 2009). Due to the aging population, the number of beneficiaries is expected to continue to grow, as will likely the health and economic burdens associated with falls.
Approximately 50%–60% of falls in older adults occur in the home (Pighills et al., 2011; Pynoos et al., 2010; Rogers et al., 2004). Those who fall are more likely to be admitted to long-term care facilities (Donald & Bulpitt, 1999), an unwanted outcome for many who want to live independently inside their own home. Approximately 90% of older adults prefer to stay in their own home as they age (American Association of Retired Persons, 2010), which is known as “aging-in-place.” Because of this, home safety and accessibility are key concerns for many older adults (National Institute on Aging, 2021). Home modifications play an important role to make homes safer to live independently (National Institute on Aging, 2021). However, according to the American Occupational Therapy Association, only approximately 16% of home owners have home modifications that would provide a safe and comfortable living environment for aging-in-place (American Occupational Therapy Association, 2020).
Home modifications are essential for older adults who are interested in aging-in-place and who want to live more independently in their own home; they have also been shown to mitigate fall risks. Improving home environments by reducing home hazards that cause tripping or slipping, and having home modifications (i.e., bathroom modifications) are essential to mitigate fall risks (Keall et al., 2015; Pighills et al., 2019; Pynoos et al., 2010; Rogers et al., 2004; Vieira et al., 2016). Additionally, home modifications have been shown to improve daily activities in older adults (Stark et al., 2009), which is vital for those who want to age-in-place.
For older adults with physical limitations, bathroom areas can be a high-risk environment, which has been found to have a high prevalence of fall occurrence (Stevens et al., 2014). Bathroom modifications, such as grab bars or a shower seat, are some of the most effective home modifications that can mitigate this issue (Bakk et al., 2017; Gitlin et al., 2006). However, home modifications in general require older adults to pay out-of-pocket (LaPlante et al., 1992). Therefore, home modifications for low-income older adults, or those with fixed incomes, can be challenging (Jon Pynoos & Mnishita, 2003).
Previous studies found associations between home modifications and factors, such as age, sex, race/ethnicity, chronic conditions, obesity, income, education, and functional/physical limitations. Racial and ethnic minorities were less likely to have home modifications (Bakk et al., 2017; Meucci et al., 2016). Females (Bakk et al., 2017; Meucci et al., 2016), older adults (Bakk et al., 2017; Harvey et al., 2014; Meucci et al., 2016; Pressler & Ferraro, 2010), those with higher educational attainment (Lin & Wu, 2014; Meucci et al., 2016), those with obesity (Pressler & Ferraro, 2010), those with chronic conditions (Bakk et al., 2017; Pressler & Ferraro, 2010; Rubin & White-Means, 2001), such as heart disease (Kim et al., 2014), those with ADL limitations (Bakk et al., 2017; Kim et al., 2014; Meucci et al., 2016), and those with worse self-reported health (Bakk et al., 2017) are more likely to have home modifications.
Although previous studies have examined factors associated with home modifications among older adults in the United States (Bakk et al., 2017; Meucci et al., 2016), Meucci et al. investigated the association between sociodemographic and economic factors and the presence of simple home modifications among older adults using the 2011 National Health and Aging Trends Study. Limited research is available that focuses on the presence of bathroom modifications among high-risk population of those who have experienced falls. Therefore, the objective of this study is to examine the following factors: predisposing, such as sex, age, race/ethnicity; enabling, such as income level and residing area; and need-related, such as chronic conditions and fear of falling variables associated with bathroom modifications among Medicare beneficiaries aged ≥65 years with at least one fall. By understanding the impacts of factors on bathroom modifications, information can be used for outreach efforts to promote and improve access to home modifications for this at-risk population who might want to age-in-place.
2 |. MATERIALS AND METHODS
2.1 |. Data and study population
We used the 2016 Medicare Current Beneficiary Survey Public Use File (MCBS PUF), which is the publicly accessible version of the Medicare Current Beneficiary Survey (Medicare Current Beneficiary Survey, 2019). The MCBS is a nationally representative survey of Medicare beneficiaries and is available as the PUF or the Limited Data Set. The MCBS PUF contains fewer variables, and some variables are recoded and merged into fewer categories (Medicare Current Beneficiary Survey, 2019). Beneficiaries’ socio-demographic characteristics, health indicators, and medical care-related data are on the individual level (Medicare Current Beneficiary Survey, 2019). Our study sample included 2,404 community-dwelling Medicare beneficiaries aged ≥65 years who reported ≥1 fall.
2.2 |. Measures
The outcome variable was bathroom modifications, a dichotomous variable with 1 = having bathroom modifications; 0 = not having bathroom modifications. The original question from MCBS PUF was (Medicare Current Beneficiary Survey, 2019): “Does [your/sample person’s (SP’s)] (house/own apartment or condominium/mobile home/place of residence) have modifications to any bathroom such as grab bars or a shower seat?” (with “yes” or “no” answer).
The independent variables included in the regression model were guided by the previous studies (Bakk et al., 2017; Meucci et al., 2016) and the Andersen Behavioral Model (Andersen, 1995) that posits that predisposing, enabling, and need-related factors affect the use of healthcare services, and has been adopted to study home modification use (Bakk et al., 2017) (home modification can be considered as an alternative to replace care or reduce the care burden that might have to be provided by caregivers). For predisposing variables, we included sex (male, female), age group (65–74, ≥75 years), race/ethnicity (non-Hispanic White, non-Hispanic Black, Hispanic and Other), education level (<high school, high school, and >high school), and marital status (married, widowed, divorced/separated, and never married). For enabling variables, we included income level (<$25,000, ≥$25,000), residing area (metro, non-metro), and living status (alone, not alone). For need-related variables, we included body mass index (BMI) (underweight BMI <18.5, healthy weight 18.5 ≤ BMI < 25.0, overweight 25.0 ≤ BMI < 30.0, obese 30 ≤ BMI < 40.0, and extremely obese BMI ≥ 40), instrumental activities of daily living and/or activities of daily living (IADL/ADL) limitations (no limitation, only IADLs limitation, 1–2 ADL limitations, 3–4 ADL limitations, and 5–6 ADL limitations); general health status (excellent/very good, good, and fair/poor); fear of falling scale (not at all afraid falling/a little afraid of falling, moderately afraid of falling/afraid of falling, and very afraid of falling/extremely afraid of falling); and 11 comorbidities (i.e., repeated falls [having ≥2 falls], high blood pressure, diabetes, myocardial infarction/heart attack, stroke/brain haemorrhage, rheumatoid arthritis, osteoporosis/soft bones, depression, urinary incontinence, hearing issue, and vision issue). With approximately 72% of Medicare beneficiaries having ≥2 chronic conditions (Maciejewski & Hammill, 2019), the inclusion of chronic/health conditions is important. Many older adults with these health conditions need assistance with care. For example, those with heart disease may have a frail condition and may require frequent assistance from caregivers (Kim et al., 2014). Because of this, they also may need home modifications to reduce the care burden and improve access to simple activities of daily living.
2.3 |. Statistical analysis
We first calculated proportions for categorical variables. Differences in the proportions of predisposing, enabling, and need-related factors were compared between those who reported having bathroom modifications and those without by using Wald χ2 tests. Bivariate and multivariable logistic regression models were performed to examine the associations between bathroom modifications and those factors. Survey weights were applied to account for the survey design, and to ensure the accuracy of the estimates. The SAS Enterprise Guide, version 6.1 was used for the data management and STATA Stata/IC, version 11.2 was used for the data analysis.
3 |. RESULTS
A total of 2,404 Medicare beneficiaries (representing 9.4 million beneficiaries) had experienced at least one fall that were included in this study (Table 1). In the study sample, 55.5% had bathroom modifications (Table 1), and 50.1% had repeated falls (Table 2). Approximately 40.2% of those with repeated falls had no bathroom modifications (representing 1.9 million beneficiaries; not presented in the Tables). Compared between those with and without bathroom modifications, 63.0% versus 55.4% were female, 54.5% versus 32.7% were aged ≥75 years, and 82.1% versus 77.1% were non-Hispanic White (Table 1). Those with bathroom modifications had higher proportions of comorbidities (i.e., hypertension, heart attack, stroke, rheumatoid arthritis, osteoporosis, depression, urinary incontinence, visual impairment, hearing impairment), ADL/IADL limitations, fear of falling, and repeated falls than those without bathroom modifications (Table 2).
TABLE 1.
Characteristics of sociodemographic of Medicare beneficiaries aged ≥65 years with ≥1 fall by bathroom modifications status
Variable, weighted % | Total | No bathroom modifications | Bathroom modifications | p-value |
---|---|---|---|---|
N, sample size | 2,404 | 897 | 1,507 | |
Weighted number of beneficiaries | 9.4 million | 4.2 million | 5.2 million | |
Overall | 100.0 | 44.5 | 55.5 | |
Sex | 0.003 | |||
Male | 40.4 | 44.6 | 37.0 | |
Female | 59.6 | 55.4 | 63.0 | |
Age (years) | <0.001 | |||
65–74 | 55.2 | 67.3 | 45.5 | |
≥75 | 44.8 | 32.7 | 54.5 | |
Race/ethnicity | 0.042 | |||
Non-Hispanic White | 79.8 | 77.1 | 82.1 | |
Non-Hispanic Black | 6.3 | 8.1 | 4.8 | |
Hispanic | 7.6 | 8.3 | 7.0 | |
Other | 6.3 | 6.5 | 6.1 | |
Marital status | 0.001 | |||
Married | 53.1 | 55.0 | 51.5 | |
Widowed | 25.7 | 20.8 | 29.6 | |
Divorced/separated | 16.1 | 19.2 | 13.7 | |
Never married | 5.1 | 5.0 | 5.1 | |
Living status | 0.033 | |||
Not alone | 68.6 | 71.3 | 66.4 | |
Alone | 31.4 | 28.7 | 33.6 | |
Highest level of education | 0.125 | |||
Less than high school | 15.5 | 13.5 | 17.0 | |
High school | 33.1 | 34.2 | 32.2 | |
More than high school | 51.4 | 52.3 | 50.8 | |
Income | 0.090 | |||
<$25,000 | 35.8 | 33.3 | 37.9 | |
≥$25,000 | 64.2 | 66.7 | 62.1 | |
Residing area | 0.746 | |||
Metro | 76.9 | 76.6 | 77.2 | |
Non-metro | 23.1 | 23.4 | 22.8 |
Note: p-values were calculated based on Wald χ2 tests.
TABLE 2.
Characteristics of health indicators of Medicare beneficiaries aged ≥65 years with ≥1 fall by bathroom modifications status
Variable, weighted % | Total | No bathroom modifications | Bathroom modifications | p-value |
---|---|---|---|---|
Repeated falls | 0.004 | |||
No | 49.9 | 54.7 | 46.0 | |
Yes | 50.1 | 45.3 | 54.0 | |
Fear of falling | <0.001 | |||
Not at all/little afraid of falling | 49.1 | 60.0 | 40.3 | |
Moderately afraid/afraid of falling | 27.2 | 23.0 | 30.6 | |
Very/extremely afraid of falling | 23.7 | 17.0 | 29.1 | |
IADL/ADL limitations | <0.001 | |||
No functional limitations | 44.2 | 58.7 | 32.5 | |
Only IADLs | 11.8 | 10.8 | 12.7 | |
1–2 ADLs | 27.5 | 22.2 | 31.8 | |
3–4 ADLs | 10.8 | 5.8 | 14.7 | |
5–6 ADLs | 5.7 | 2.5 | 8.3 | |
Diabetes | 0.917 | |||
No | 60.7 | 60.9 | 60.6 | |
Yes | 39.3 | 39.1 | 39.4 | |
High blood pressure/hypertension | 0.024 | |||
No | 29.3 | 32.3 | 26.8 | |
Yes | 70.7 | 67.7 | 73.2 | |
Myocardial infarction/heart attack | 0.006 | |||
No | 86.3 | 88.7 | 84.4 | |
Yes | 13.7 | 11.3 | 15.6 | |
Stroke/brain haemorrhage | <0.001 | |||
No | 86.7 | 90.0 | 84.1 | |
Yes | 13.3 | 10.0 | 15.9 | |
Rheumatoid arthritis | 0.020 | |||
No | 81.2 | 84.1 | 78.9 | |
Yes | 18.8 | 15.9 | 21.1 | |
Osteoporosis | <0.001 | |||
No | 78.4 | 82.9 | 74.8 | |
Yes | 21.6 | 17.1 | 25.2 | |
Depression | 0.005 | |||
No | 67.2 | 70.7 | 64.4 | |
Yes | 32.8 | 29.3 | 35.6 | |
Urinary incontinence | <0.001 | |||
No | 49.9 | 58.0 | 43.3 | |
Yes | 50.1 | 42.0 | 56.7 | |
Visual impairment | <0.001 | |||
No trouble | 59.4 | 62.4 | 57.1 | |
A little trouble | 35.4 | 34.2 | 36.3 | |
A lot of trouble | 5.1 | 3.3 | 6.6 | |
Hearing impairment | 0.001 | |||
No trouble | 46.4 | 48.0 | 45.2 | |
A little trouble | 44.9 | 46.1 | 43.8 | |
A lot of trouble | 8.7 | 5.9 | 11.0 | |
BMI | 0.116 | |||
BMI <18.5 | 1.9 | 1.7 | 2.1 | |
18.5 ≤ BMI < 25 | 28.8 | 26.7 | 30.6 | |
25 ≤ BMI < 30 | 33.3 | 36.3 | 30.9 | |
30 ≤ BMI < 40 | 30.8 | 30.7 | 30.8 | |
BMI ≥40 | 5.1 | 4.5 | 5.6 | |
General health | <0.001 | |||
Excellent/very good | 40.6 | 44.5 | 37.4 | |
Good | 31.9 | 33.3 | 30.8 | |
Fair/poor | 27.5 | 22.1 | 31.8 |
Note: p-values were calculated based on Wald χ2 tests. Percentages may not total 100% due to rounding.
Abbreviations: BMI, body mass index; IADL/ADL, instrumental activities of daily living/activities of daily living.
Table 3 presents the results of the bivariate and multivariable logistic regression models used to predict factors associated with having bathroom modifications. The odds of having bathroom modifications were significantly lower for non-Hispanic Blacks (odds ratio [OR] = 0.38, 95% confidence interval [CI] = 0.24, 0.59, p < 0.001) and Hispanics (OR = 0.64, 95% CI = 0.41, 0.97, p = 0.039) when compared with the reference category of non-Hispanic Whites (Table 3). Lower odds of having bathroom modifications were reported for beneficiaries with divorced/separated status (OR = 0.54, 95% CI = 0.35, 0.83, p = 0.006) compared with those with a married status. Beneficiaries aged ≥75 years had 2.18 times (95% CI = 1.77, 2.68, p < 0.001) the odds of having bathroom modifications than those in the younger age-group. Those living alone had 1.41 times (95% CI = 1.00, 1.97, p = 0.047) the odds of having bathroom modifications than those not living alone (Table 3).
TABLE 3.
Unadjusted and adjusted odds ratios (95% confidence interval) of associations between bathroom modifications and socio-demographics and health conditions
Unadjusted odds ratios (95% confidence interval) | p-value | Adjusted odds ratios (95% confidence interval) | p-value | |
---|---|---|---|---|
Sex | ||||
Female | Reference | Reference | ||
Male | 0.73 (0.59–0.89) | 0.002 | 0.81 (0.62–1.07) | 0.142 |
Age (years) | ||||
65–74 | Reference | Reference | ||
≥75 | 2.46 (2.06–2.95) | <0.001 | 2.18 (1.77–2.68) | <0.001 |
Race/ethnicity | ||||
Non-Hispanic White | Reference | Reference | ||
Non-Hispanic Black | 0.55 (0.37–0.81) | 0.003 | 0.38 (0.24–0.59) | <0.001 |
Hispanic | 0.79 (0.55–1.13) | 0.206 | 0.64 (0.41–0.97) | 0.039 |
Other | 0.88 (0.57–1.36) | 0.578 | 0.70 (0.44–1.09) | 0.110 |
Marital status | ||||
Married | Reference | Reference | ||
Widowed | 1.51 (1.18–1.94) | 0.001 | 0.81 (0.56–1.17) | 0.262 |
Divorced/separated | 0.76 (0.57–1.02) | 0.071 | 0.54 (0.35–0.83) | 0.006 |
Never married | 1.09 (0.63–1.89) | 0.736 | 0.83 (0.43–1.56) | 0.552 |
Living status | ||||
Not alone | Reference | Reference | ||
Alone | 1.25 (1.02–1.55) | 0.033 | 1.41 (1.00–1.97) | 0.047 |
Highest level of education | ||||
Less than high school | Reference | Reference | ||
High school | 0.74 (0.56–0.98) | 0.039 | 0.89 (0.64–1.25) | 0.500 |
More than high school | 0.77 (0.57–1.04) | 0.098 | 1.22 (0.84–1.80) | 0.290 |
Income | ||||
≥$25,000 | Reference | Reference | ||
<$25,000 | 1.22 (0.96–1.55) | 0.091 | 1.05 (0.79–1.37) | 0.741 |
Residing area | ||||
Non-metro | Reference | Reference | ||
Metro | 1.03 (0.82–1.30) | 0.748 | 1.05 (0.77–1.43) | 0.741 |
Diabetes | ||||
No | Reference | Reference | ||
Yes | 1.01 (0.80–1.26) | 0.918 | 0.97 (0.75–1.26) | 0.814 |
High blood pressure/hypertension | ||||
No | Reference | Reference | ||
Yes | 1.30 (1.03–1.63) | 0.025 | 1.15 (0.89–1.49) | 0.262 |
Myocardial infarction/heart attack | ||||
No | Reference | Reference | ||
Yes | 1.45 (1.10–1.91) | 0.009 | 1.43 (1.06–1.94) | 0.020 |
Stroke/brain haemorrhage | ||||
No | Reference | Reference | ||
Yes | 1.69 (1.24–2.30) | 0.001 | 1.11 (0.79–1.56) | 0.537 |
Rheumatoid arthritis | ||||
No | Reference | Reference | ||
Yes | 1.41 (1.05–1.90) | 0.023 | 1.21 (0.86–1.70) | 0.261 |
Osteoporosis | ||||
No | Reference | Reference | ||
Yes | 1.63 (1.30–2.06) | <0.001 | 1.15 (0.88–1.50) | 0.289 |
Depression | ||||
No | Reference | Reference | ||
Yes | 1.33 (1.08–1.64) | 0.007 | 1.05 (0.83–1.32) | 0.690 |
Urinary incontinence | ||||
No | Reference | Reference | ||
Yes | 1.80 (1.47–2.21) | <0.001 | 1.29 (1.01–1.65) | 0.039 |
Visual impairment | ||||
No trouble | Reference | Reference | ||
A little trouble | 1.15 (0.93–1.43) | 0.170 | 0.97 (0.77–1.23) | 0.849 |
A lot of trouble | 2.17 (1.42–3.32) | <0.001 | 1.00 (0.60–1.67) | 0.973 |
Hearing impairment | ||||
No trouble | Reference | Reference | ||
A little trouble | 1.00 (0.80–1.25) | 0.950 | 0.78 (0.60–1.02) | 0.070 |
A lot of trouble | 1.97 (1.25–3.12) | 0.004 | 1.07 (0.63–1.80) | 0.801 |
BMI | ||||
Underweight, BMI <18.5 | Reference | Reference | ||
Healthy, 18.5 ≤ BMI < 25 | 0.94 (0.45–1.99) | 0.890 | 0.89 (0.43–1.84) | 0.752 |
Overweight, 25 ≤ BMI < 30 | 0.70 (0.33–1.51) | 0.367 | 0.79 (0.36–1.71) | 0.555 |
Obese, 30 ≤ BMI < 40 | 0.83 (0.38–1.80) | 0.636 | 0.86 (0.39–1.87) | 0.700 |
Extreme or high-risk obesity, BMI ≥40 | 1.02 (0.42–2.48) | 0.950 | 0.90 (0.36–2.24) | 0.833 |
General health | ||||
Excellent/very good | Reference | Reference | ||
Good | 1.09 (0.83–1.44) | 0.509 | 0.84 (0.60–1.15) | 0.278 |
Fair/poor | 1.70 (1.31–2.23) | <0.001 | 0.89 (0.64–1.25) | 0.521 |
Fear of falling | ||||
Not at all/little afraid of falling | Reference | Reference | ||
Moderately afraid/afraid of falling | 1.99 (1.56–2.53) | <0.001 | 1.44 (1.09–1.91) | 0.011 |
Very/extremely afraid of falling | 2.53 (1.93–3.31) | <0.001 | 1.55 (1.13–2.14) | 0.007 |
IADL/ADL limitations | ||||
No functional limitations | Reference | Reference | ||
Only IADLs | 2.12 (1.51–2.97) | <0.001 | 1.75 (1.18–2.60) | 0.006 |
1–2 ADLs | 2.58 (2.01–3.32) | <0.001 | 2.11 (1.53–2.92) | <0.001 |
3–4 ADLs | 4.59 (3.04–6.94) | <0.001 | 3.73 (2.20–6.31) | <0.001 |
5–6 ADLs | 6.03 (3.31–10.98) | <0.001 | 4.72 (2.32–9.61) | <0.001 |
Repeated falls | ||||
No | Reference | Reference | ||
Yes | 1.41 (1.11–1.78) | 0.004 | 1.10 (0.84–1.45) | 0.444 |
Note: Unadjusted and adjusted odds ratios were estimated from the bivariate and multivariable logit regression model, respectively.
Abbreviations: BMI, body mass index; IADL/ADL, instrumental activities of daily living/activities of daily living.
Those with myocardial infarction/heart attack (OR = 1.43, 95% CI = 1.06, 1.94, p = 0.020) and urinary incontinence (OR = 1.29; 95% CI = 1.01, 1.65, p = 0.039) had higher odds of having bathroom modifications (Table 3). Both the fear of falling and ADL limitations had incremental impacts on having bathroom modifications. The odds of having a bathroom modification was higher among those with self-reported moderate (OR = 1.44; 95% CI = 1.09, 1.91, p = 0.011) and very/extremely (OR = 1.55; 95% CI = 1.13, 2.14, p = 0.007) fear of falling than those with no/little fear of falling. The odds of having bathroom modifications increased as the number of ADL limitations increased from 1–2 ADLs (OR = 2.11, 95% CI = 1.53, 2.92, p < 0.001), 3–4 ADLs (OR = 3.73, 95% CI = 2.20, 6.31, p < 0.001), to 5–6 ADLs (OR = 4.72, 95% CI = 2.32, 9.61, p < 0.001) compared with those with no functional limitations. Those with only IADLs (OR = 1.75, 95% CI = 1.18, 2.60, p = 0.006) were also associated with having bathroom modifications compared with those without functional limitations. Those with repeated falls were not significantly associated with having bathroom modifications (OR = 1.10; 95% CI = 0.84, 1.45, p = 0.444).
4 |. DISCUSSION
Our study revealed that age, race/ethnicity, living status, and marital status were associated with having bathroom modifications. Results showed that Medicare beneficiaries with health conditions, such as myocardial infarction/heart attack and urinary incontinence, had higher odds of having bathroom modifications. The fear of falling and ADL limitations had incremental impacts on whether an older adult would have a bathroom modification. These findings can be used to inform decisions concerning the allocation of assistance or resources promoting home modifications for those who might need them, as home modification is a key component for aging-in-place.
Our findings are consistent with previous studies examining factors associated with having home modifications in the United States (Bakk et al., 2017; Meucci et al., 2016). Similar to previous research, factors such as age, race/ethnicity, marital status, living status, and ADL limitations were associated with having home modifications (Bakk et al., 2017; Meucci et al., 2016). Compared with previous research, we also found that urinary incontinence, and fear of falling was associated with home modifications. However, contrary to previous research, we did not find education level or sex associated with home modifications (Bakk et al., 2017; Meucci et al., 2016). These differences could be a result of different study populations and model specifications. Our study population were specifically Medicare beneficiaries, an at-risk population who have experienced falls. Based on our preliminary findings during model specifications using forward/backward selection, urinary incontinence, and fear of falling had a competing impact on home modifications with sex. Once they were added into the model, sex became insignificant, with or without covariates. The urinary incontinence and fear of falling variables likely have a more dominant impact on home modifications than sex for this at-risk study population.
Regarding education, the explanation is more complex, as chronic conditions and other health-related variables (i.e., myocardial infarction/heart attack, stroke, arthritis, osteoporosis, urinary incontinence, hearing/visual impairment, general health, and ADL limitations) affected the result of educational attainment (based on our preliminary findings). This is likely because of the conflicting impacts of education and chronic conditions on home modifications—those with higher educational attainment are more likely to be healthier with less chronic conditions; therefore, they are less likely to need home modifications. However, those with chronic conditions are more likely to need home modifications. This dynamic likely explains the result of the education variable that we observed. Our study population consists of primarily older adults with chronic conditions, which may have more impact on the need of home modifications than educational attainment. However, further research is needed to untangle interactions between these variables.
Our study showed a significant racial and ethnic difference in having bathroom modifications. A higher proportion of non-Hispanic White beneficiaries reported bathroom modifications, compared with non-Hispanic Blacks and Hispanics. The disparities may be a result of healthcare disparities among minorities that have been widely reported. Reports have shown the disparities in health and health care among minority Medicare beneficiaries (Center for Medicare Advocacy, 2021; Martino et al., 2020). Racial and ethnic disparities in health and healthcare can be attributed to structural barriers, such as residing in areas where access to health care or specialty care are less available (National Research Council, 2004), and providers’ biases of treatments and practices (Institute of Medicine, 2003). Of note, the number of minorities age 65 years or older is expected to increase from 11.8 million in 2017 to 27.7 million in 2040 (Administration for Community Living [ACL], 2018). The population of non-Hispanic Whites aged 65 years or older is expected to increase by only 36%, whereas Hispanics are expected to grow by 188% and non-Hispanic Blacks by 96% between 2017 to 2040 (ACL, 2018). This estimated increase in the number of older minorities can potentially exacerbate the disparity of having bathroom modifications that we observed in the current study. Therefore, reducing disparities should be considered to prevent potential subsequent negative health and economic outcomes, assuming they all have the same need.
For other demographic characteristics, advanced age, marital status (i.e., being divorced/separated), and living alone were associated with bathroom modifications. In general, the findings are consistent with previous studies (Bakk et al., 2017; Meucci et al., 2016). The lower odds of having bathroom modifications among those divorced/separated compared with married beneficiaries were likely because of financial constraints and possible a new living arrangement as a result of a divorce or separation. On the other hand, those living alone had higher odds, which could possibly be from the autonomy of the individuals’ desire to live independently.
The association of advanced age and bathroom modifications can be explained from the interrelationship between age, falls, and reduced functionality. The CDC National Center for Injury Prevention and Control lists a safe home environment as a fall prevention strategy (Centers for Disease Control and Prevention, 2017), and the use of home modifications on reducing fall risks and supporting daily living for older adults has been reported (Clemson et al., 2008; Maggi et al., 2018). Certain home modifications, such as grab bars in showers, could substantially prevent falls and support independent living (Gitlin et al., 2006; Tchalla et al., 2012), and a safe home environment is commonly recommended to older adults to prevent falls by occupational therapists (Maggi et al., 2018).
Chronic conditions, such as urinary incontinence, myocardial infarction/heart attack, and ADL limitations, were associated with bathroom modifications. As older adults have more ADL-related limitations, it is not surprising that they have higher odds of having home modifications. This can be attributed to the ability to manage their home environment and perform self-care—the level of ADL limitations therefore reflect the level of need for home modifications (National Aging In Place Council, 2021). Myocardial infarction/heart attack often results in physical and functional impairments, and individuals who have had such an event need assistance from caregivers for daily activities; therefore, they need home modifications for themselves (Stewart, 2013) and to reduce caregiver burden. Finally, for those with urinary incontinence, the association with bathroom modifications are most likely from the inconvenient and disruptive nature of the condition.
These conditions also have been found to be associated with falls (Chiarelli et al., 2009; Tan & Kenny, 2006; Tromp et al., 2001). Because many older adults who have chronic conditions often experience falls, they may need to see healthcare providers, such as occupational therapists. Occupational therapists often include home modifications as a part of fall prevention interventions for individuals who are at higher risk of falls during home environment assessments (Maggi et al., 2018). Other chronic conditions, such as diabetes, were not associated with home modification. It is possible that these other conditions could play mediating roles on home modifications. Further research is needed to better understand the interactions of those conditions with home modifications. However, no associations were observed by Kim et al. (2014) as well. Prevention efforts to reduce or prevent these chronic conditions are important.
Because the current study focused on Medicare beneficiaries with at least one fall, the fear of falling scale was included. We found that fear of falling had an incremental impact on having bathroom modifications. Fear of falling is also known to be associated with falls and other negative health-related consequences, such as reduced functional ability and quality of life (Li et al., 2003; Scheffer et al., 2008), and bathroom modifications have been shown to reduce the fall risk. Therefore, older adults with an increased fear of falling had a higher likelihood of having bathroom modifications. We found that repeated falls were not associated with bathroom modifications, and approximately 40% of beneficiaries with repeated falls had no bathroom modifications. This is noteworthy because home modifications have been shown to reduce fall risks.
Home modifications for optimal aging-in-place can enable older adults to stay in their own home longer. In fact, they can provide an additional 5–10 years (Bayer, 2000; Lawlor & Thomas, 2008) and are a possible cost-effective alternative than a long-term care facility for older adults (Kim et al., 2014). However, some of the home modifications can be a financial burden for underserved populations, and Medicare has strict and very limited coverage for home modifications, if any (“How to make & pay for home modifications to enable aging in place, 2021; “Everything Medicare covers around the house,” 2020). For example, in theory, home modifications such as grab bars may be covered by Medicare only if it is deemed medically necessary with professional assessments (e.g., medical providers/occupational therapists) and under Medicare durable medical equipment coverage (“How to make & pay for home modifications to enable aging in place, 2021; “Everything Medicare covers around the house,” 2020). Unfortunately, if home modifications are deemed to be only a prevention or assistance measure and not medically necessary, Medicare beneficiaries would then need to pay out of pocket (“Everything Medicare covers around the house,” 2020). Therefore, this is a barrier to accessing home modifications, especially for underserved Medicare beneficiaries. Finally, our findings of factors associated with home modifications and disparities in home modifications among at-risk populations can be used to inform decision makers on possibly relevant policies related to home modifications that may support aging-in-place (e.g., to improve or streamline coverage benefit for home modifications for those in need [those with repeated falls]) (Kim et al., 2014).
4.1 |. Limitations
There are limitations that should be acknowledged. The question, “Does SP Bathroom have Modifications” in the survey only provided information on whether the respondent had a bathroom modification or not. However, the survey did not specifically ask about the modification types, such as a raised toilet seat, grab bar, or non-slip floor and place of modification, such as a tub, toilet, or shower. Secondly, the survey did not mention whether the recorded fallings occurred before or after installing bathroom modifications. Future iterations of the survey with this additional information would be beneficial, as it would allow researchers to evaluate the fall prevention effect of bathroom modifications more specifically. The location of where the older adult fell was not collected in the survey. A more specific question about falls (or repeated falls) that occurred in the bathroom areas would be ideal. Finally, MCBS predefined categories of variables. For instance, the income variable only had two categories. Having more detailed categories of variables could yield different results.
Our study found various demographic factors and health-related conditions associated with bathroom modifications. Broader accessibility of home modifications for Medicare beneficiaries, especially among non-Hispanic Blacks and Hispanics, should be considered, especially for those with higher fall risks, to provide a safe home environment for those who desire aging-in-place. Further studies are needed to examine older adults’ attitudes toward bathroom modifications, and cost effectiveness of bathroom modifications to prevent falls and aging-in-place for this at-risk population.
What is known about this topic?
Factors associated with home modifications for older adults are known; however, limited information is available on factors associated with bathroom modifications for older adults who experience falls.
What this paper adds?
Over 55% of Medicare beneficiaries who experience falls had bathroom modifications. However, 40% of those with repeated falls (≥2 falls) had no bathroom modifications.
In the adjusted model, non-Hispanic Blacks and Hispanics had lower odds of having bathroom modifications than non-Hispanic Whites. Fear of falling and activities of daily living limitations were associated with bathroom modifications.
Improving disparities in bathroom modifications for older minorities, including those with repeated falls, is vital for fall prevention efforts and aging-in-place.
Funding information
No financial disclosures were reported by the authors of this paper.
Footnotes
CONFLICT OF INTEREST
None declared.
DATA AVAILABILITY STATEMENT
The data that support the findings of this study are openly available at https://www.cms.gov/Research-Statistics-Data-and-Systems/Downloadable-Public-Use-Files/MCBS-Public-Use-File.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data that support the findings of this study are openly available at https://www.cms.gov/Research-Statistics-Data-and-Systems/Downloadable-Public-Use-Files/MCBS-Public-Use-File.