Abstract
This study examined the relationship between visual impairments and individual ADLs and IADLs among community-dwelling older adults.
Normal aging can cause visual function to deteriorate, leading to a decline in the ability to clearly see objects (Christ et al., 2014). The prevalence of visual impairment and blindness is expected to nearly double between 2015 and 2050 because of increased longevity and the increased incidence of disease among aging individuals (Varma et al., 2016). More specifically, in the United States, the nationwide prevalence of people living with vision loss or blindness is estimated to be 7.08 million. This rate has increased from 0.99% among the population ages 50 to 54 yr to 20.73% among those age 85 yr and older, indicating a significant rise in prevalence with increased age (Flaxman et al., 2021).
Previous studies have consistently highlighted the close association between visual impairment among older adults and negative health outcomes, as well as limitations in functional status (Christ et al., 2014; Lam et al., 2013). As individuals age, maintaining adequate visual function becomes increasingly important to maintain independence in daily activities (Christ et al., 2014). Preserving sight could mean wearing eyeglasses. However, visual aids such as glasses do not continue to be effective for all people, especially for those with visual diseases (e.g., age-related macular degeneration) that can progress significantly and cause a decline in visual function that cannot be corrected.
As a result of visual dysfunction, individuals report challenges in independently performing activities of daily living (ADLs) and instrumental activities of daily living (IADLs; Naël et al., 2017; Sloan et al., 2005; West et al., 2002). Interestingly, older adults with visual impairment have greater difficulties with IADLs than with ADLs (Kee et al., 2021). Specifically, a decline in near visual acuity has been identified as a significant factor contributing to the increased prevalence of IADL impairment among older adults (Kee et al., 2021). In addition, longitudinal studies have reported on the trajectory of decline in visual acuity and its impact on IADL difficulties over time (Lam et al., 2013). These studies have demonstrated that the progressive deterioration of visual acuity is associated not only with short-term functional impairments but also with long-term increases in IADL limitations and constraints on social engagement. For instance, near visual acuity and distance visual acuity have been shown to be related to complications in preparing meals, managing finances, and driving (Naël et al., 2017; Sloan et al., 2005). Also, among a group of women, worse contrast sensitivity has been reported to be associated with worse performance of IADLs and medication management, in specific the ability to fill a pillbox quickly (Windham et al., 2005). Another study reported that worse contrast sensitivity was associated with worse physical performance, as measured with the Short Physical Performance Battery (Thompson et al., 2023).
Although vision impairment is an independent risk factor for performance of ADLs and IADLs, there has been a lack of research broadly examining the relationship between specific and multiple types of vision impairment and multiple and specific types of ADLs and IADLs with a nationally representative sample. For instance, findings from previous studies have limitations in that they used overall vision scores or self-reported vision measurements, many of which consist of only one Likert-scale question, rather than specifically measuring multiple vision domains, for example, visual fields or low-luminance visual acuity (Haymes et al., 2002; Hreha et al., 2021; Sloan et al., 2005). Additionally, the results of older studies were based on relatively small samples and older datasets (Haymes et al., 2002; Kee et al., 2021; Owsley et al., 2001; Sloan et al., 2005). Therefore, there is a need to address these gaps to further understand whether specific vision impairments are independently associated with performance of specific types of ADLs and IADLs.
We aimed to address these limitations by using current, nationally representative data from the United States and examining the associations among three specific vision function domains—distance visual acuity, near visual acuity, and contrast sensitivity—and individual ADLs tasks (dressing, toileting, bathing, eating) and IADL tasks (laundry, shopping, making hot meals, money management, self-management of medications) among community-dwelling older adults. We also examined the relationships between socio demographic and health-related characteristics and ADLs and IADLs.
Method
Study Data
The National Health and Aging Trends Study (NHATS) is a nationally representative panel survey administered to Medicare beneficiaries ages 65 yr and older in the United States (Freedman et al., 2022). Commencing in 2011, the NHATS began its data collection efforts by conducting initial interviews with a cohort of participants. In 2015, the study was expanded through the inclusion of replenishment participants, and researchers continued to conduct annual in-person interviews with the combined group of original and replenishment participants. In 2021, the NHATS began gathering new data, including objective visual and auditory assessment data collected using tablet-based tests (Hu et al., 2022). Three vision assessments (i.e., distance visual acuity, near visual acuity, and contrast sensitivity) were assessed under binocular conditions, accounting for each participant’s use of eyeglasses or contact lenses (Hu et al., 2022). Our study used publicly available deidentified data, and it was exempt from any requirement for ethical clearance by the Yonsei University Mirae Institutional Review Board (Approval No. 1041849-202307-SB-127-01).
Participants
We used the 2022 NHATS participant data in conjunction with data from tablet-based vision tests to construct the analysis dataset. From the initial 2022 NHATS dataset total of 6,327 participants, we retrieved a final dataset consisting of 4,947 community-dwelling older adults. Figure 1 displays the selection procedures used to obtain our final cohort.
Flow diagram of selection procedures for 2022 NHATS participant data.
Dependent Variables
Our nine dependent variables were four ADLs (dressing, toileting, bathing, eating) and five IADLs (laundry, shopping, making hot meals, money management, self-management of medications). We use the term money management instead of handling bills and banking in this article for the sake of clarity. We defined whether participants were independent or not in each activity. All ADLs and IADLs were rated on a dichotomous scale (0 = dependent or difficult, 1 = independent).
Independent Variables
We used the visual function–derived variables created from the objective vision measurements, which were provided in the NHATS vision and hearing activities user guide (Hu et al., 2022). The three visual function variables were distance vision (with scores ranging from –0.1 logMAR to 1.1 logMAR), near vision (with scores ranging from –0.21 logMAR to 1.54 logMAR), and contrast sensitivity (with scores ranging from 0.4 logCS to 2.0 logCS), 1 and these variables were recoded as a continuous variable in the NHATS database. For distance vision and near vision, higher scores indicate worse function; conversely, for contrast sensitivity, higher scores indicate better function.
Covariates
The study’s covariates were sociodemographic characteristics and health-related characteristics. These covariates were chosen on the basis of previous studies, which included indicators related to visual function, ADLs, and IADLs (Desrosiers et al., 2009; Kiyoshige et al., 2019; Sloan et al., 2005). The categorical variables were age (1 = 65–69 yr; 2 = 70–74 yr; 3 = 75–79 yr; 4 = 80–84 yr; 5 = 85–89 yr; 6 = ≥90 yr), sex (0 = female; 1 = male), race/ethnicity (1 = White; 2 = Black; 3 = other non-Hispanic; 4 = Hispanic), marital status (1 = married or living with partner; 2 = separated, divorced, or widowed; 3 = never married), educational attainment (1 = less than high school; 2 = high school; 3 = beyond high school), cataract surgery history (0 = no; 1 = yes), and dementia (1 = probable dementia; 2 = possible dementia; 3 = no dementia; Kasper et al., 2013). The continuous variables were scores on the Patient Health Questionnaire–2 (PHQ–2; scores ranged from 2 to 8), which was used to measure depressive disorders, and the two-item Generalized Anxiety Disorder (GAD–2; scores ranged from 2 to 8), which was used to measure anxiety disorders. Higher scores on the PHQ–2 and GAD–2 indicated worse psychological status.
Statistical Analysis
We used descriptive statistics to examine sociodemographic and health-related characteristics. Continuous variables (PHQ–2, GAD–2, near visual acuity, distance visual acuity, and contrast sensitivity) were expressed as means and standard deviation, and categorical variables (age, sex, race/ethnicity, marital status, educational attainment, and dementia) were expressed as frequencies and percentages. A series of multivariable logistic regression analyses were then used to estimate the relationship between visual function and independence status with respect to ADLs and IADLs. For descriptive statistics, statistical significance was determined with an α level of .05. The logistic regression results were presented as odds ratios (ORs) with 95% confidence intervals (CIs). We used SAS statistical software (Version 9.4) for all statistical analyses and data management.
Results
Table 1 presents the demographic characteristics of the study participants. The majority of the participants were between 75 and 79 yr old (n = 1,310; 26.5%), female (n = 2,803; 56.7%), and White (n = 3,231; 65.3%). For near visual acuity, the mean score was 0.22 (minimum = –0.21, maximum = 1.54); for distance visual acuity, 0.13 (minimum = –0.10, maximum = 1.10); and for contrast sensitivity, 1.67 (minimum = 0.04, maximum = 2.00).
Descriptive Statistics for the Sample of Community-Dwelling Older Adults (N = 4,947)
Note. GAD–2 = 2-item Generalized Anxiety Disorder; max = maximum; min = minimum; PHQ–2 = Patient Health Questionnaire–2.
Visual Function and Independence in ADLs and IADLs
Table 2 presents the results of the multivariable logistic regression analysis examining the relationship between visual function and independence in ADLs. Near visual acuity was significantly associated with eating (OR = 0.29, 95% CI [0.13, 0.65]). However, distance visual acuity was not significantly associated with any of the ADLs. Contrast sensitivity was significantly associated with dressing (OR = 2.23, 95% CI [1.51, 3.30]), toileting (OR = 2.20, 95% CI [1.29, 3.76]), and bathing (OR = 1.61, 95% CI [1.06, 2.46]).
Multivariable Logistic Regression Analysis Examining the Relationship Between Visual Function and Independence in ADLs Among Older Adults
Note. ADLs = activities of daily living; CI = confidence interval; GAD–2 = 2-item Generalized Anxiety Disorder; OR = odds ratio; PHQ–2 = Patient Health Questionnaire–2; Ref. = reference category.
Table 3 presents the results of a multivariable logistic regression analyses examining the relationship between visual function and independence in IADLs. Near visual acuity was significantly associated with all IADLs except self-management of medications. Distance visual acuity was significantly associated with shopping (OR = 0.50, 95% CI [0.31, 0.79]) and money management (OR = 0.55, 95% CI [0.34, 0.87]). Contrast sensitivity was significantly associated with laundry (OR = 1.44, 95% CI [1.03, 2.00]), shopping (OR = 1.61, 95% CI [1.16, 2.24]), making hot meals (OR = 2.08, 95% CI [1.50, 2.89]), and self-management of medications (OR = 1.65, 95% CI [1.13, 2.41]).
Multivariable Logistic Regression Analysis Examining the Relationship Between With Visual Function and Independence in IADLs Among Older Adults
Note. CI = confidence interval; GAD–2 = 2-item Generalized Anxiety Disorder; IADLs = instrumental activities of daily living; OR = odds ratio; PHQ–2 = Patient Health Questionnaire–2; Ref. = reference category.
Sociodemographic Characteristics, Health-Related Characteristics, and Independence in ADLs and IADLs
As shown in Tables 2 and 3, women were more independent than men in all IADLs except shopping, whereas participant sex was not significant in any of the ADLs except eating. For all of the IADLs except self-management of medications, age was significant in three age groups: 80 to 84 yr, 85 to 89 yr, and 90 yr and older. Additionally, age was found to be significant for laundry in all age groups. In all IADLs, individuals who were separated, divorced, widowed, or never married were more independent compared with those who were married or living with a partner, with the exception of self-management of medications, for which the never-married group did not show a significant difference. Higher PHQ–2 and GAD–2 scores were associated with lower independence in all ADLs and IADLs. Individuals with probable or possible dementia were less independent than those without dementia in all ADLs and IADLs.
Discussion
Impaired vision is an important health burden. Understanding the relationship between specific types of vision impairments, rather than vision impairment generally, and performance of specific ADLs and IADLs is crucial in order to plan for steps that can be taken in rehabilitation. In particular, strategies may be implemented to help overcome functional challenges. Therefore, we set out to investigate these variables and found that this cohort’s visual impairment status was related to their performance of ADLs and IADLs in multiple ways.
First, for all ADLs, we found that poor near visual acuity was specifically related to worse functioning on one ADL item: eating. Clear vision is essential to identify food on a plate and locate utensils for successful eating. Dressing, toileting, and bathing all have aspects that require the ability to see close up to perform the task well. For example, seeing detail helps to determine the orientation of a shirt to be able to wear it correctly.
Haymes et al. (2002) have reported similar findings that clinical vision impairment measures, such as visual acuity, are highly correlated with capacity to perform ADLs. We also found that higher contrast sensitivity scores were related to better ADL performance scores. In addition, being able to see the difference between two similar colors or shades of gray, an example of low contrast, is necessary for strong performance of ADLs. For example, the task of bathing requires a person to perform in a low-contrast environment. Bathtubs are often white, and bathroom floors are often the same or a similar color. Good contrast sensitivity is key to know where the floor ends and the bathtub begins so that one can step in safely. It is also needed to find a white bar of soap in a white soap dish. Colenbrander and Fletcher (2006) investigated contrast sensitivity among a group of patients with low vision. Similar to our findings, participants’ overall ADL scores were influenced equally by visual acuity and contrast sensitivity, and there was a trend toward contrast sensitivity scores correlating with worse scores for ADLs (Colenbrander and Fletcher, 2006).
Second, regarding all IADLs, we found that worse near visual acuity was related to worse functioning with laundry, shopping, and money management. This is understandable because, for example, people need to see the small lettering on laundry dials to successfully complete the task of laundry. Another example of near visual acuity’s role in IADLs is during shopping. People need to be able to identify what items they are purchasing at the store, but food containers usually have very small print and low contrast. In terms of money management, people need to see bills and bank documents, which also usually have small print, to complete all aspects of financial management. Kee et al. (2021) similarly found that impairment in near visual acuity is a significant factor contributing to IADL impairment among older adults.
Naël et al. (2017) and Sloan et al. (2005) found that near visual acuity is related to difficulties in preparing meals, managing finances, and driving. Additionally, these researchers found that difficulty with distance visual acuity was related to difficulties in managing finances (Naël et al., 2017; Sloan et al., 2005). We also found that worse distance visual acuity was related to worse performance in shopping and money management. This finding is logical because good distance vision is crucial for engaging in activities such as independent shopping, in which people often need to visually access signs at the ends of shopping aisles to navigate effectively.
Third, we found that higher contrast sensitivity scores were related to better scores in laundry, shopping, and making hot meals. This is somewhat similar to what homemaking might entail, which has been reported to be influenced more by contrast sensitivity than by visual acuity in a group of individuals with low vision (Colenbrander and Fletcher, 2006). Again, this finding is logical and appears to be important for good performance of specific IADLs that require engagement with objects that might be the same color as the background color (low contrast). In addition, better contrast sensitivity has been found to be associated with better medication management (Windham et al., 2005), which we also found.
We found that depression, anxiety, and dementia were associated with increased functional difficulties with both ADLs and IADLs. Other researchers have also found that independence in ADLs and IADLs is associated with sociodemographic factors, depression, anxiety, and dementia (Beltz et al., 2022; Connolly et al., 2017; Tomioka et al., 2017). Additionally, the negative associations of these health-related mental and cognitive factors with both ADLs and IADLs were consistent with findings in previous studies (Bleijenberg et al., 2017; Hesseberg et al., 2013). We found that individuals’ challenges with ADLs and IADLs increased with age, with more age groups experiencing difficulties with IADLs in particular. These results are consistent with those of previous studies that have found that good performance of IADLs is more challenging than good performance of ADLs and that difficulties may increase with age (Kiyoshige et al., 2019; Millán-Calenti et al., 2010).
Our study had several limitations. Its design was cross-sectional, which makes it difficult to determine the cause of visual function decline. In other words, the limited scope of vision-related questions in the NHATS database does not allow us to understand the prevalence of age-related conditions (e.g., glaucoma, optic neuropathy) among study participants, nor does it report on other vision conditions, such as hemianopsias. However, given that the majority of participants fell in the 75 to 79 yr age range, it is likely that age- related conditions, such as macular degeneration, contributed to their visual impairment. Future studies with longitudinal data should examine the specific causes of visual impairment and report on those conditions extensively. In addition, NHATS findings often reflect expected declines in vision with age, although they can sometimes highlight specific aspects that differ from typical ranges reported in clinical settings. For example, NHATS data may reveal a higher incidence of vision impairment due to underreporting or undiagnosed cases, particularly among individuals who lack access to regular eye care. Also, because this was an observational retrospective study, we have no information on whether participants were using coping strategies such as varying lighting quality, which could have contributed to better performance of ADLs or IADLs. Although those limitations were inherent to secondary survey databases, a strength of our study lies in its observance of the relationships between distance visual acuity, near visual acuity, and contrast sensitivity, separately, and the following ADLs and IADLs: dressing, toileting, bathing, eating, laundry, shopping, making hot meals, money management, and self-management of medications. Future studies could address these limitations to achieve a more accurate and comprehensive understanding of the functional consequences of vision impairment.
Implications for Occupational Therapy Practice
This study provides further evidence that specific visual impairments, particularly those involving near visual acuity and contrast sensitivity, are closely linked to older adults’ ability to perform ADLs and IADLs. The findings confirm the importance of addressing these visual functions in occupational therapy practice to support the independence of community-dwelling older adults.
Conclusion
Using data from a national database, we found relationships between specific types of visual function (near visual acuity, distance visual acuity, and contrast sensitivity) and performance of specific ADLs and IADLs. This study is unique because of the multiple types of vision impairment captured and the many different ADLs and IADLs reported in the data, which provides granular-level information about an issue that is prevalent among the older adult population. These results serve as a valuable reminder for occupational therapy practitioners of the significance of taking visual function into account when caring for older adults in multiple practice settings. Addressing vision is essential especially because it relates to participation in ADLs and IADLs. In essence, it is important to incorporate a visual screen that includes both objective and self-report measures so that practitioners can accurately refer individuals for further testing. After assessment, practitioners can most likely better engage clients in the appropriate interventions to support older adults with specific types of visual dysfunction to enhance their functional abilities. Furthermore, a referral to a low vision occupational therapist or an optometrist may be necessary if the visual impairment is more severe and requires specialized intervention outside the occupational therapist’s scope of practice or comfort level.
Footnotes
1The abbreviation logMAR stands for logarithm of the minimum angle of resolutions, whereas the abbreviation logCS stands for contrast sensitivity as a function of time.
Acknowledgments
Medical editor Katharine O’Moore-Klopf, ELS (East Setauket, NY), provided professional English-language editing of this article. This work was supported by grant funding from National Center for Medical Rehabilitation Research, National Institute of Child Health and Human Development (K01HD106010).