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The Prevalence and Trends of Instrumental Activities of Daily Living Impairments in the United States from 2008–2018

Abstract

Background:

Instrumental activities of daily living (IADL) are neuropsychological-driven tasks that are linked to cognitive dysfunction. Examining population-based IADL deficits may reveal insights for the presence of these impairments in the United States.

Objective:

This investigation sought to evaluate the prevalence and trends of IADL impairments in Americans.

Methods:

A secondary analysis of data from the 2006–2018 waves of the Health and Retirement Study was conducted. The overall unweighted analytic sample included 29,764 Americans aged≥50 years. Respondents indicated their ability to perform six IADLs: manage money, manage medications, use a telephone, prepare hot meals, shop for groceries, and use a map. Persons reporting difficulty or an inability to complete an individual IADL were considered as having a task-specific impairment. Similarly, those indicating difficulty or an inability to perform any IADL were classified as having an IADL impairment. Sample weights were utilized to generate nationally-representative estimates.

Results:

Having an impairment in using a map (2018 wave: 15.7% (95% confidence interval (CI): 15.0–16.4) had the highest prevalence in individual IADLs regardless of wave examined. The overall prevalence of IADL impairments declined during the study period (p < 0.001) to 25.4% (CI: 24.5–26.2) in the 2018 wave. Older Americans and women had a consistently higher prevalence of IADL impairments compared to middle-aged Americans and men, respectively. The prevalence of IADL impairments was also highest among Hispanics and non-Hispanic Blacks.

Conclusion:

IADL impairments have declined over time. Continued surveillance of IADLs may help inform cognitive screening, identify subpopulations at risk of impairment, and guide relevant policy.

INTRODUCTION

Older Americans currently account for approximately 17% of the total United States population [1]. This growing older American demographic is projected to reach 98 million, nearly 25% of the United States population by the year 2060 [2]. Many older Americans are living with age-related morbidities, which in turn, threaten quality of life, independence, and longevity [3]. Therefore, population surveillance of such morbidities is critical for monitoring trends, informing healthcare providers, and guiding policy efforts and interventions to better serve the health needs of the growing older American population.

Alzheimer’s disease and related dementias (ADRD) are a type of age-related morbidity that is projected to increase in line with the older growing American population [4]. Instrumental activities of daily living (IADL) are neuropsychological-driven tasks that, when impaired, may indicate onset cognitive decline and physical disablement [5]. IADLs are sensitive to cognitive declines because they are uniquely linked to several mental processes [6]. For example, executive functions that are crucial to cognitive functioning such as organization and planning contribute to managing medications and shopping for groceries [7]. Accordingly, IADLs are considered a feasible clinical and epidemiological indicator of cognitive function [6–8].

Questionnaires and interviews may serve as screening tools for referral to more sophisticated cognitive assessments [9]. However, dementia screening is not consistently recommended during routine geriatric health assessments [10]. Assessing a patients’ ability to perform IADLs could be easily implemented in such routine health assessments because of their health-related predictive utility [11]. Given that IADLs are feasible to assess and connected to cognitive function [12], examining the prevalence and trends of IADL impairments may help to uncover additional trends in cognitive functioning. We sought to examine the prevalence and trends of IADL impairments in Americans.

MATERIALS AND METHODS

Participants

A secondary analysis of data from the 2006–2018 waves of the Health and Retirement Study (HRS) was conducted for this investigation. The 2006 wave was selected based on the concluding year of IADL prevalence estimates from other reports [13], while the 2018 wave included the most recent wave of available data from the HRS. Distinct HRS datafiles were joined to the RAND HRS dataset as needed [14]. The overarching purpose of the HRS is to observe the economic and health status of Americans over time [14]. HRS participation requires persons be aged at least 50 years, and new birth cohorts are included in the HRS every six years for maintaining national representation [14]. Those in the HRS are re-interviewed biannually and followed until death. Response rates have consistently been > 80% [15].

The HRS utilizes a multistage probability design, including geographical stratification and oversampling for select demographic groups [16]. Participants provided written informed consent prior to entering the HRS, and the University’s Behavioral Sciences Committee Institutional Review Board approved protocols. More details about the HRS are available elsewhere [16].

Measures

Age, sex, race, and ethnicity were reported at each wave. Respondents also communicated with trained interviewers at each wave about their ability to perform six IADLs: manage money, manage medications, use a telephone, prepare hot meals, shop for groceries, and use a map. Persons reporting difficulty or an inability to complete an individual IADL were considered as having an impairment in that specific task. Likewise, those indicating difficulty or an inability to perform any IADL were classified as having an IADL impairment.

Statistical analysis

All analyses were conducted with SAS 9.4 software (SAS Institute; Cary, NC). HRS analytic guidelines steered our analyses [17]. Survey weights, which accounted for the complex sampling design, where used to obtain nationally representative estimates. Descriptive characteristics were presented unweighted as mean±standard deviation for continuous variables or frequency (percentage) for categorical variables as indicated to increase interpretability. Prevalence estimates for Americans with impairments in individual IADL tasks were presented at each wave, and the overall prevalence of IADL impairments were similarly shown at each wave. IADL impairment prevalence estimates were then stratified by age group (50–64 years (middle-aged);≥65 years (older)), sex (male, female), and race and ethnicity (Hispanic, non-Hispanic Black, non-Hispanic Other, non-Hispanic White). Prevalence estimates were weighted and presented alongside 95% confidence intervals (CI).

Separate multilevel logistic regression models for examining trends in IADL impairments were conducted with the survey weights included for overall impairments, age group, sex, and race, and ethnicity. To account for the longitudinal design, repeated measures of individual participants in multiple waves were modelled using a random intercept for each participant. For each model, the binary outcome was IADL impairment. For the overall model, the only predictor was time (i.e., survey wave). For assessing trends by age group, the model adjusted for time, age group (reference: middle-aged), and the interaction between time and age group. Similarly, for the model of trends by sex, the model adjusted for time, sex (reference: female), and time-by-sex interaction. In the final model, there was a predictor for time, race, and ethnicity (reference group: non-Hispanic White) and the interaction between time andrace/ethnicity.

As another supplementary analysis, we performed an unweighted crude, cross-sectional multilevel logistic regression model to examine the association between IADL impairment and cognitive impairment. A random intercept for individuals was included. Cognitive functioning was determined with a modified version of the Telephone Interview of Cognitive Status (TICS) [18]. Persons aged<65 years and≥65 years with TICS scores≤11 and≤10 had a cognitive impairment, respectively [19–21]. This supplementary analysis necessitated that we include the TICS, which is a separate measure from our principal analyses, and therefore, n = 1,410 participants were removed from this individual analysis for not having TICS scores. An alpha level of 0.05 was used for all analyses.

RESULTS

The overall unweighted baseline descriptive characteristics of the 29,764 participants are shown in Table 1. Participants were aged 63.8±10.9 years and were mostly female (56.5%). Table 2 presents the overall prevalence of individual IADL impairments. At each wave, the prevalence of Americans with impairments in using a map was highest, while impairments in managing medications were often lowest. Table 3 shows the overall prevalence of IADL impairments. The prevalence of IADL impairments trended downward over time (p < 0.001), such that IADL impairments were 31.9% (CI: 31.1, 32.7) in the 2006 wave, estimates trended downward to 25.4% (CI: 24.5, 26.2) in the 2018 wave.

Table 1

Unweighted overall baseline descriptive characteristics of the participants

Overall
(n = 29,764)
Age (y)63.8±10.9
Age Category (n (%))
  Middle-Aged Adult (n (%))17,312 (58.2)
  Older Adult (n (%))12,452 (41.8)
Sex (n (%))
  Male (n (%))12,959 (43.5)
  Female (n (%))16,805 (56.5)
Race and Ethnicity (n (%))
  Hispanic4,072 (13.7)
  Non-Hispanic Black5,845 (19.6)
  Non-Hispanic Other1,192 (4.0)
  Non-Hispanic White18,655 (62.7)

Results are presented as mean±standard deviation or frequency (percentage) as indicated.

Table 2

Overall prevalence of individual instrumental activities of daily living impairments

Weighted FrequencyWeighted Prevalence95% CI
ImpairedImpaired (%)
2006 Wave
  Manage Money7,718,31810.09.5, 10.5
  Manage Medications3,294,4014.34.0, 4.6
  Use a Telephone3,790,6574.94.6, 5.3
  Prepare Hot Meals8,260,66810.710.2, 11.2
  Shop for Groceries9,897,67612.912.3, 13.4
  Use a Map15,832,65120.619.9, 21.2
2008 Wave
  Manage Money7,312,48810.09.5, 10.5
  Manage Medications3,228,2014.44.1, 4.8
  Use a Telephone3,731,8505.14.8, 5.4
  Prepare Hot Meals7,596,20110.49.9, 10.9
  Shop for Groceries8,720,05511.911.4, 12.5
  Use a Map14,899,37220.419.7, 21.0
2010 Wave
  Manage Money9,043,2359.69.1, 10.1
  Manage Medications3,806,9394.03.7, 4.4
  Use a Telephone4,605,7334.94.6, 5.2
  Prepare Hot Meals8,113,6468.68.2, 9.1
  Shop for Groceries10,105,89610.710.2, 11.2
  Use a Map15,789,38816.816.2, 17.4
2012 Wave
  Manage Money8,116,7659.08.5, 9.4
  Manage Medications3,589,3334.03.7, 4.3
  Use a Telephone4,234,5074.74.3, 5.0
  Prepare Hot Meals7,925,2208.78.3, 9.2
  Shop for Groceries9,604,50010.610.1, 11.1
  Use a Map14,948,41916.515.9, 17.1
2014 Wave
  Manage Money8,170,7279.59.0, 10.0
  Manage Medications3,707,8984.33.9, 4.6
  Use a Telephone4,253,1874.94.6, 5.3
  Prepare Hot Meals7,463,7998.68.2, 9.1
  Shop for Groceries9,279,32910.710.2, 11.3
  Use a Map15,234,39617.617.0, 18.3
2016 Wave
  Manage Money9,385,6678.78.2, 9.2
  Manage Medications4,260,2013.93.6, 4.3
  Use a Telephone4,459,8654.13.8, 4.4
  Prepare Hot Meals8,455,5377.87.4, 8.3
  Shop for Groceries10,737,6049.99.4, 10.4
  Use a Map16,161,85915.014.4, 15.6
2018 Wave
  Manage Money8,567,5118.37.8, 8.9
  Manage Medications3,689,5183.63.2, 3.9
  Use a Telephone4,245,2894.13.8, 4.5
  Prepare Hot Meals7,923,3177.77.2, 8.2
  Shop for Groceries10,206,5119.99.3, 10.5
  Use a Map16,183,19415.715.0, 16.4
Table 3

Overall prevalence of instrumental activities of daily living impairments

Weighted Frequency ImpairedWeighted Prevalence (%)95% CI
2006 Wave24,572,73031.931.1, 32.7
2008 Wave23,013,98331.530.6, 32.3
2010 Wave25,825,10827.426.7, 28.2
2012 Wave24,075,75626.625.8, 27.3
2014 Wave24,140,31027.927.1, 28.7
2016 Wave26,696,87024.724.0, 25.5
2018 Wave26,152,93825.424.5, 26.2

Table 4 presents the prevalence of IADL impairments by age group. Older Americans had a higher prevalence of IADL impairments compared to middle-aged Americans at each wave. For example, the prevalence of IADL impairments in middle-aged Americans was 19.2% (CI: 17.9–20.4) in 2018, while the corresponding IADL impairment prevalence in older Americans was 31.3% (CI: 30.2–32.5). Additionally, a downward trend in the prevalence of IADL impairments was observed in older Americans (p < 0.001), but not in those who were middle-aged.

Table 4

Prevalence of instrumental activities of daily living impairments by age group

Weighted Frequency ImpairedWeighted Prevalence (%)95% CI
Middle-Aged
  2006 Wave8,872,80722.020.8, 23.1
  2008 Wave7,378,92821.119.8, 22.4
  2010 Wave10,637,62019.818.8, 20.8
  2012 Wave8,693,11318.217.2, 19.2
  2014 Wave8,215,44020.118.9, 21.3
  2016 Wave10,649,35518.017.0, 19.0
  2018 Wave9,786,47419.217.9, 20.4
Older
  2006 Wave15,699,92342.741.7, 43.7
  2008 Wave15,635,05540.839.8, 41.8
  2010 Wave15,187,48837.436.4, 38.5
  2012 Wave15,382,64335.734.7, 36.8
  2014 Wave15,924,87034.933.8, 35.9
  2016 Wave16,047,51532.731.6, 33.8
  2018 Wave16,366,46431.330.2, 32.5

The prevalence of IADL impairments by sex are shown in Table 5. Females had a higher prevalence of IADL impairments at each wave compared to males. In the 2018 wave, females had a IADL impairment prevalence at 29.8% (CI: 28.6–30.9), while males had an IADL impairment prevalence at 20.2% (CI: 19.0–21.4). Nonetheless, the prevalence of IADL impairments significantly declined during the study period for both males and females (p < 0.01). Table 6 presents the prevalence of IADL impairments by race and ethnicity. Persons identifying as Hispanic and non-Hispanic Black had the highest prevalence of IADL impairments compared to non-Hispanic Whites. The prevalence of IADL impairments decreased over time for persons categorized as Hispanic, non-Hispanic Black, and non-Hispanic White (p < 0.001), but not non-Hispanic Other. Appendix 1 shows the results of the IADL impairment trends analyses. The results of the supplementary analysis examining IADLs and cognitive impairment showed that persons with an IADL impairment had 2.14 (CI: 2.04–2.24) greater odds for cognitive impairment.

Table 5

Prevalence of instrumental activities of daily living impairments by sex

Weighted Frequency ImpairedWeighted Prevalence (%)95% CI
Females
  2006 Wave15,323,15336.235.1, 37.3
  2008 Wave14,600,17936.335.1, 37.4
  2010 Wave16,234,55731.730.7, 32.7
  2012 Wave15,050,33730.529.5, 31.5
  2014 Wave15,254,07732.431.3, 33.5
  2016 Wave16,794,10628.927.8, 30.0
  2018 Wave16,499,16029.828.6, 30.9
Males
  2006 Wave9,249,57726.625.4, 27.8
  2008 Wave8,413,80425.524.3, 26.7
  2010 Wave9,590,55122.321.2, 23.3
  2012 Wave9,025,41921.820.7, 22.9
  2014 Wave8,886,23322.521.3, 23.6
  2016 Wave9,902,76419.818.7, 20.8
  2018 Wave9,653,77820.219.0, 21.4
Table 6

Prevalence of instrumental activities of daily living by race and ethnicity

Weighted Frequency ImpairedWeighted Prevalence (%)95% CI
Hispanic
  2006 Wave2,704,61946.743.7, 49.7
  2008 Wave2,464,56944.041.0, 47.0
  2010 Wave3,016,28839.336.6, 42.0
  2012 Wave2,978,60638.635.9, 41.3
  2014 Wave3,180,42642.039.0, 44.9
  2016 Wave3,784,89834.932.5, 37.3
  2018 Wave3,963,40637.835.0, 40.5
Non-Hispanic Black
  2006 Wave3,217,19745.342.9, 47.6
  2008 Wave2,903,11242.740.2, 45.1
  2010 Wave3,902,15341.139.0, 43.2
  2012 Wave3,577,30239.237.0, 41.3
  2014 Wave3,672,13942.239.9, 44.5
  2016 Wave3,960,72234.932.8, 36.9
  2018 Wave3,921,68636.033.8, 38.3
Non-Hispanic Other
  2006 Wave721,47435.129.6, 40.7
  2008 Wave726,83137.731.7, 43.6
  2010 Wave937,11629.425.0, 33.9
  2012 Wave857,82127.122.8, 31.3
  2014 Wave918,88830.125.5, 34.7
  2016 Wave1,399,16825.021.4, 28.7
  2018 Wave1,448,27127.022.8, 31.1
Non-Hispanic White
  2006 Wave17,929,44028.828.0, 29.7
  2008 Wave16,919,47128.727.8, 29.6
  2010 Wave17,969,55124.323.5, 25.1
  2012 Wave16,662,02723.622.7, 24.4
  2014 Wave16,368,85724.323.4, 25.2
  2016 Wave17,552,08221.820.9, 22.7
  2018 Wave16,819,57522.021.0, 23.0

DISCUSSION

Our results indicate that approximately a quarter of Americans aged at least 50-years are living with an IADL impairment, and from 2006–2018, the prevalence of such impairments have generally declined. When examining task-specific IADLs, the prevalence of impairment in using a map were highest. The prevalence of IADL impairments were greatest in older Americans and females. Moreover, Hispanics and non-Hispanic Blacks had the highest prevalence of IADL impairments. Our findings provide insights into the presence of IADL impairments among United States adults, and how IADL impairments have changed over time. While opportunities may exist for improving how we assess IADLs, examining IADLs remains a simple screening method for cognitive impairment and age-related disablement.

The decline of IADL impairments overtime could be attributed to recent technological and medical advancements. Impairments in using a map reign as the most prevalent IADL impairment in Americans, but its prevalence has generally declined the most compared to the other IADLs over time. With sophistication in technologies, the ability to disseminate and use a map may have declined in relevance. Global Positioning Systems (i.e., GPS), which are currently found on most mobile devices, may replace the need for a person to utilize spatial awareness skills for reading a map [22]. Replacing this technologically unsuitable IADL with an appropriate modern-day substitution may better serve clinicians when screening for cognitive dysfunction and recognize the true functional capacity of their patient. The prevalence of impairments in shopping for groceries and preparing hot meals have similarly shown noteworthy declines during the period examined. A possible explanation might be within Americans’ increased use of convenience foods prepared outside of the home [23].

IADL impairments tend to increase with age, and thus it was not surprising that our findings indicated older adults had a higher prevalence of IADL impairments compared to middle-aged persons. Our findings of a higher prevalence of IADL impairments in females may be associated with the high prevalence of cognitive impairment in said population [24, 25]. Several studies indicate that females have a higher prevalence of cognitive impairment compared to males possibly due to socio-economic status, psychosocial factors, cardiovascular and metabolic diseases, sex hormone changes in midlife, genetics, and lack of educational opportunities [24, 25]. Changing gender and societal norms in America may also influence the acquired IADL impairment prevalence disparity between males and females. The high prevalence of IADL impairments in Hispanic and non-Hispanic Blacks may be due to health disparities and lack of access to care [26, 27]. IADLs in this regard may be best observed in tandem with observing the personal narratives and social determinants of health and quality of life. Such issues persist within a pattern of health determinants, outcomes, and resources associated with social inequities, such as social exclusion, blocked opportunities, or unequal returns on effort within societal structures [28]. Structural equation models have also shown that psychosocial factors are related to both social determinants and healthoutcomes [29].

IADLs remain a simple-to-collect indicator of cognitive dysfunction and physical disablement. While the prevalence of IADLs in American adults should continue being monitored, we also recommend that the current tasks included in IADL assessments be modernized. For example, the ability to use a map could be outdated such that technological advancements have decreased the relevance of this task. Possible refinement of IADLs to be modernized could be especially important as technological resources continue advancing and middle-aged persons phase into older adulthood. Moreover, not all individual IADL impairments have equal health-related severity, and as refinements to IADLs might be considered, acknowledging how each task is linked to future health should be contemplated [30]. Regardless, the surveillance of neuropsychological-driven tasks such as IADLs will continue providing insights into cognitive impairment.

Some limitations should be noted. Although self-report information is common for population-based studies such as HRS and IADL assessments, self-report biases may have nevertheless existed in our findings. While we chose to limit the stratified analyses to age, gender, and race and ethnicity for interpretability, other sub-group analyses may have relevance and should be considered in future investigations. Our principal results did not examine the association between IADLs and cognitive dysfunction, but future work may examine these associations more closely, including how individual IADLs and basic self-care tasks might be linked to cognitive impairment. Despite these limitations, our investigation revealed IADL impairment prevalence and trends in American adults using population-representative data, with weighted prevalence estimates at each wave. We recommend IADLs continue to be surveilled alongside other cognitive indicators as the older American demographic increases to help inform screening andintervention.

Conclusions

The overall prevalence of IADL impairments, which is a strong marker of cognitive function, have declined from 2006–2018 in Americans aged at least 50 years. Older adults and females showed greater IADL impairment prevalence compared to middle-aged adults and males, respectively. Additionally, the prevalence of IADL impairments were greatest in Hispanics and non-Hispanic Blacks. Examining IADLs remains a simple method for initial screenings of cognitive dysfunction and disablement during aging. Insights into the presence of IADL impairments among Americans, and how IADL impairments continue changing over time are important to inform healthcare providers as early detection of IADL impairment provides a critical window for implementation of a targeted cognitive function intervention.

ACKNOWLEDGMENTS

The authors have no acknowledgments to report.

FUNDING

Research reported in this publication was supported by the National Institute on Aging of the National Institutes of Health under Award Number R15AG072348 (to RM) and R01AG075117 (to JMH). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

CONFLICT OF INTEREST

The authors have no conflict of interest to report.

SUPPLEMENTARY MATERIAL

[1] The supplementary material is available in the electronic version of this article: https://dx.doi.org/10.3233/ADR-220107.

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