Research in Gerontological Nursing

Empirical Research 

Productive Activities But Not Paid Work Relate to Well-Being in Older Adults

Knar Sagherian, PhD, RN; Karen Rose, PhD, RN; Shijun Zhu, DrE, MS; Ha Do Byon, PhD, RN; Kathryn Crawford, RN


Productive activity engagement may positively contribute to the subjective well-being (SWB) of older adults during retirement. The current study explored the relationships between paid work and productive activities and SWB in Medicare beneficiary older adults predominantly living in the community. The 2015-2016 data (N = 2,916) from the National Health and Aging Trends Study were used. Multiple linear regressions with complex survey data were performed. Aside from paid work, the productive activities included in the analyses were volunteer work, caregiving role, social participation, online networking, and physical activity. After controlling for health-related, sociodemographic, and baseline SWB variables, three productive activities, but not paid work, were significantly related to SWB. Older adults who were physically active, engaged in volunteer work, and had increased social participation had significantly increased SWB. These findings encourage older adults to remain physically active and engage when possible in productive activities that are more social than economic in nature. [Research in Gerontological Nursing, 14(1), 24–32.]


Productive activity engagement may positively contribute to the subjective well-being (SWB) of older adults during retirement. The current study explored the relationships between paid work and productive activities and SWB in Medicare beneficiary older adults predominantly living in the community. The 2015-2016 data (N = 2,916) from the National Health and Aging Trends Study were used. Multiple linear regressions with complex survey data were performed. Aside from paid work, the productive activities included in the analyses were volunteer work, caregiving role, social participation, online networking, and physical activity. After controlling for health-related, sociodemographic, and baseline SWB variables, three productive activities, but not paid work, were significantly related to SWB. Older adults who were physically active, engaged in volunteer work, and had increased social participation had significantly increased SWB. These findings encourage older adults to remain physically active and engage when possible in productive activities that are more social than economic in nature. [Research in Gerontological Nursing, 14(1), 24–32.]

Subjective well-being (SWB), generally defined as overall satisfaction with life (evaluative view), self-realization or meanings attributed to life (eudaimonic view), or happiness and pleasure related to personal experiences (hedonic view) (Diener et al., 2017; Ryan & Deci, 2001), is related to better health outcomes in the older adult population. Findings from research studies have demonstrated that higher levels of SWB are related to faster recovery from physical and mental illness (Lamers et al., 2012), better self-reported health and sleep (Steptoe et al., 2008), and lower likelihood of mortality (Sadler et al., 2011; Saunders et al., 2018). Thus, promotion and maintenance of SWB in late life, perhaps by means of practical activities, becomes significant. National longitudinal studies, such as the Health and Retirement Study and the National Health and Aging Trends Study (NHATS), collect data on SWB to study its trends and inform public policy decisions and health care services.

Overall, activity engagement in late life plays a protective role in the SWB of older adults. Activity theory of aging suggests that older adults who remain active and engaged in productive meaningful activities and maintain social interactions during role transitions, particularly into retirement, will have higher levels of SWB or increased life satisfaction (Diggs, 2008). These productive activities are considered to be personally rewarding and socially valued and generally have economic (e.g., paid work, volunteer work, caregiving role) and more recently social (e.g., visiting family or friends, going to clubs or exercising, attending religious services) characteristics (Thanakwang & Isaramalai, 2013). An earlier U.S. study found that older adults who had a greater number of and more time spent on productive activities had significantly increased SWB measured as happiness (Baker et al., 2005). Another U.S. study found that older women who were engaged in volunteer work and religious activities had increased positive well-being (Waddell & Jacobs-Lawson, 2010). Increased internet use among older adults was also related to better psychological well-being (Heo et al., 2015).

At times, the nature of productive activities may be more sedentary. For example, findings from a study from Taiwan showed that older adults who were engaged in active and sedentary leisure activities experienced higher levels of SWB over time (Ku et al., 2016). A population-based study among community-dwelling older adults from southern Germany showed that being physically inactive increased the odds for poor SWB (Lukaschek et al., 2017). Regarding paid work activity among U.S. older adults, which is projected to increase substantially in coming years (Toossi & Torpey, 2017), studies have shown that being engaged in paid and/or volunteer work as part of a number of productive activities was positively associated with various types of SWB (Baker et al., 2005; Fekete et al., 2020), and at times the independent relationship between paid work and SWB was not significant (Fekete et al., 2019). Paid work (full-time = ≥1,680 hours per year) and volunteering for <100 hours per year in older adults showed less decline in SWB measured by depressive symptoms (Hao, 2008).

Prior research has examined the relationships between productive activities and SWB. Studies have operationalized the construct of SWB as overall life satisfaction (Ku et al., 2016), positive well-being (Lukaschek et al., 2017; Waddell & Jacobs-Lawson, 2010), and depressive symptoms (Hao, 2008), or as a multifaceted approach with life satisfaction, happiness, and depressive symptoms (Baker et al., 2005), and happiness, purpose in life, and social well-being (Son & Wilson, 2012). These multiple ways of measuring SWB have resulted in mixed results, which encumbers the ability to make practical recommendations for older adults to perform certain activities that are more beneficial than others. Interestingly, some studies have found that happiness (hedonic view) and self-realization (eudaimonic view) are highly interrelated and that they may be considered a single concept (Kim et al., 2016; Tennant et al., 2007). In addition, many studies have not reported different work activities separately where their independent effects may differ on SWB. To our knowledge, no other studies have evaluated the independent effects of paid work and other productive activities in one study with a simpler approach of measuring SWB in the older adult population.

Following the theoretical underpinnings of activity theory of aging, we fill these gaps by revisiting the independent relationships in one study with current NHATS data and use a unidimensional brief measure of SWB that consists of hedonic and eudaimonic views. Our study aimed to explore the roles of paid work and productive activities (e.g., volunteer work, caregiving, social participation, online social activity, physical activity) on SWB after 1-year follow up using a national U.S. sample of older adults aged ≥65 years from community and residential non-nursing home settings. The main hypothesis was being engaged in paid work activities, independent of other productive activities, contributes to increased SWB in older adults.


Data and Sample

The NHATS is an ongoing longitudinal study that aims to better understand the disability trends and age-related functional changes in older adults from community, residential care, and nursing home settings. The NHATS was initiated in 2011 with a nationally representative sample of 8,245 Medicare beneficiaries aged ≥65 years residing in the United States. The NHATS collects data annually through face-to-face interviews and, at times, interviews proxy respondents on behalf of participants who are unable to answer the questions because of health or memory problems. In 2015, the NHATS replenished the original sample with 4,182 new participants following the same stratified three-stage sampling design (DeMatteis et al., 2017).

The current study focused on the replenished sample and included 2015 and 2016 waves of data. Initially, 3,726 community-dwelling older adults who did not live in nursing homes (n = 233 excluded) were identified who personally answered the interview surveys (n = 223 proxies excluded). Proxy respondents were excluded because the SWB scale was administered to participants only. By 2016, 3,072 participants had survived (n = 118 deceased, n = 536 lost to follow up) and a total sample of 2,985 participants had answered the follow-up interview surveys. The study further excluded 69 participants because of missing data on the outcome of SWB at follow up. The analytic sample comprised 2,916 participants.


Subjective Well-Being (Outcome). SWB was measured by seven items: four items addressed positive and negative feelings (feeling cheerful, bored, full of life, and upset) and three items addressed self-realization (life has meaning and purpose, feels confident and good about self, and likes current living situation) with reference to the past 1 month. Responses for the positive and negative feeling items were never, rarely, some days, most days, and every day. Responses for the self-realization items were agree not at all, agree, agree a little, and agree a lot. Negatively worded items were reverse coded and all seven items were summed (range = 0 to 22), with higher scores indicating greater SWB. Originally, the NHATS had adapted eight SWB items from the Psychological Well-Being Scale (Ryff & Keyes, 1995). However, Freedman et al. (2014) found one-factor structure of seven SWB items with loadings ≥0.47 and demonstrated that the reliability of the scale was acceptable (Cronbach's alpha = 0.74). In our sample, the SWB items at 2015 and 2016 time points had acceptable internal consistency; Cronbach's alpha was 0.73 and 0.74, respectively.

Productive Activity. We operationalized productive activity among older adults beyond the traditional view of creating goods or service values to encompass activities that have social value and personal benefits. The list of activities that the NHATS asked participants about were paid work, volunteering, social participation activity, online social activity, caregiving, and physical activity.

Paid work activity status (yes or no) was derived from two items that asked whether participants performed any work for pay in the past 1 week or were absent from work in the past 1 week. Participants who reported being retired or negatively responded to both items were categorized into the non-working/retiree group (i.e., no). This definition of paid worker status follows the U.S. Current Population Survey that is aligned with the NHATS.

For volunteering activity, one item asked participants if they performed any volunteer work in the past 1 month (yes or no). Social participation activity included four items, including visiting family or friends; attending religious services; participating in clubs, classes, or other organized activities; and going out for enjoyment (e.g., to a movie, to dinner, to listen to music, to see a play, to gamble) in the past 1 month. These activities were combined (summed score range = 0 to 4) and classified into three categories: 0 to 1, 2 to 3, and 4.

For online social activity, one item asked participants about their online visits to social network websites, such as Facebook® or LinkedIn®, to keep in touch with friends in the past 1 month (yes or no). The caregiving activity item asked whether participants provided care to a person, either an adult or child, in the past 1 month (yes or no). For physical activity, two items were used that asked participants about walking for exercise and performing vigorous activities that increased heart rate respiratory effort (i.e., working out, swimming, running or biking, or playing a sport) in the past 1 month. Respondents who answered yes to both or any one of the items were considered to be physically active (yes or no).


Health variables as possible covariates were chosen based on the relevant literature (Ku et al., 2016; Lukaschek et al., 2017; Steptoe et al., 2008) and consisted of multimorbidity, insomnia, fatigue, depressive symptoms, memory recall, and obesity.

Multimorbidity. The variable multimorbidity was computed as the total count of 10 health conditions reported by physicians to participants. The health conditions were heart attack, heart disease, high blood pressure, arthritis, osteoporosis, diabetes mellitus, lung disease, stroke, dementia or Alzheimer's disease, and cancer.

Insomnia. The symptoms for insomnia included difficulty falling asleep (i.e., takes >30 minutes to fall asleep) and difficulty maintaining sleep (i.e., has trouble falling back asleep) in the past 1 month. Each item was scored as 1 for responses of every night, most nights, and some nights or 0 for responses of rarely and never. The scores were summed to represent three categories: none, one symptom, and two symptoms.

Fatigue. One dichotomous (yes or no) item asked participants if they had low energy or were easily exhausted in the past 1 month.

Depressive Symptoms. Participants completed the Patient Health Questionnaire-2 (PHQ-2), which measures the frequency of having little interest or pleasure in doing things, and feeling down, depressed, or hopeless in the past 1 month. A total score ≥3 on the PHQ-2 (range = 0 to 6) is indicative of major depression. The psychometric properties of the PHQ-2 are established in the literature (Kroenke et al., 2003).

Memory Recall. The memory status of participants was assessed by the 10-word recall test administered twice within 5 minutes apart. Recall scores can range from 0 to 20, and values ≤–1.5 SD from the sample mean indicated poor memory (cutoff recall score ≤3) (Kasper et al., 2013).

Obesity. Body mass index (BMI) of participants was calculated based on their self-reported height and weight. A value of 25 kg/m2 to 29.9 kg/m2 was considered overweight and ≥30 kg/m2 was considered obese.

Sociodemographic Characteristics. Demographic variables were age in five categories (65 to 69, 70 to 74, 75 to 79, 80 to 84, and ≥85 years), sex (male, female), and race (White, Black, other). The social variables were marital status (married/with a partner and separated/divorced/never married/widowed) and education (below high school, high school, some college, college and higher, unknown/refused). Annual income was divided into quartiles (<$19,000; ≥$19,000 to $35,000; >$35,000 to $65,200; >$65,200).

Statistical Analysis

This secondary data analysis used publicly available data from the NHATS (access and was determined as exempt from the University of Tennessee Knoxville Institutional Review Board. All statistical analyses were conducted in STATA software version 15.1.

Using linear regression, SWB in 2016 was regressed on covariates including 2015 baseline SWB. Linear regression assumptions for linearity, multivariate normality, and multicollinearity were explored with no observed violations. The variables paid and volunteer work, insomnia and depressive symptoms, fatigue, recall, caregiving, BMI, education, race, and baseline SWB had missing observations. Multiple imputation by chained equations approach with 20 imputations was used to handle missing data. Survey weights of the year 2016 were used to account for different probabilities of selection, such as oversampling for Black race and older age groups and nonresponse bias, and complex survey design. Multiple hierarchical linear regression was used to examine the relationships between paid work, productive activities, and SWB. The regression model was adjusted for health variables (i.e., multimorbidity, insomnia, fatigue, depressive symptoms, memory recall, and obesity) followed by sociodemographic variables (i.e., age, sex, race, marital status, income, and education), and baseline 2015 SWB divided into tertiles. The statistical models with each adjustment retained covariates with p ≤ 0.20. The statistical significance level was set at 0.05.


The results are based on the weighted sample. As shown in Table 1, older adults on average had 2.25 health problems (SD = 1.47) and approximately 11% had depressive symptoms. More than one half had no fatigue and either reported one or two insomnia symptoms, whereas approximately 6% had impairment in recall memory. Table 2 presents the different types of activities. Older adults overall participated in a variety of productive activities. Approximately 21% of the sample had worked for pay and 29% had participated in volunteer work. Three quarters of the sample was physically active, and a small proportion of older adults did not participate in social activities (12%). On average, older adults had SWB scores at 2015 baseline of 17.52 (SD = 3.15) and at follow up of 17.1 (SD = 3.28), which were similar and considered to be relatively high.

Sociodemographic and Health Characteristics of Older Adults

Table 1:

Sociodemographic and Health Characteristics of Older Adults

Different Types of Engaged Activities and Subjective Well-Being (SWB) in Older Adults

Table 2:

Different Types of Engaged Activities and Subjective Well-Being (SWB) in Older Adults

Table 3 presents the relationships between productive activities and future SWB. Paid work activity was not associated with SWB in the adjusted models. There were also no significant relationships of SWB with caregiving or online social activities. After controlling for health, sociodemographic, and baseline SWB factors (see Model 4), older adults who volunteered, participated in social activities, and were physically active had significantly higher SWB. The final model was parsimonious and significant with four activity predictors and nine covariates (F[24, 53.9] = 136.8, p < 0.001).

Relationships Between Engaged Activities and Subjective Well-Being (SWB) in Older Adults at 1-Year Follow Up

Table 3:

Relationships Between Engaged Activities and Subjective Well-Being (SWB) in Older Adults at 1-Year Follow Up


The current findings did not support the main hypothesis that older adults who were engaged in paid work had significantly better SWB than retirees or non-workers. On the contrary, Tang et al. (2018), in a large sample of slightly younger Chinese older adults (mean age = 63.02 years, SD = 9.32), showed that being employed was related to higher life satisfaction (i.e., evaluative well-being). Nikolova and Graham (2014), using data from the United States and nine European countries, showed that older adults (age ≥66 years) who were working voluntarily part-time and full-time had higher hedonic (i.e., happiness and smiling) well-being, and overall satisfaction with personal health when compared to retirees. These studies support the positive nature of some type of paid work activity and flexible employment options among older adults' in late life well-being. Lack of significance between paid work and SWB in the current study may be related to missing information around the complexity of held jobs, duration of work hours, years of work experience, and motivations for postponed retirement that may influence the outcome. These motivations may be beyond monetary as older adults with higher income (>$65,200) in our sample were more likely to have paid work activity. Another probable reason is the definition of paid work activity, despite congruency with employment status from the U.S. Current Population Survey, may not fully capture the other important factors related to employment status (e.g., work schedule, flexibility in work structures), which may have affected our findings. In addition, baseline assessment of employment status does not adequately measure possible work changes, such as work status and schedules in consecutive months, prior to SWB follow up. Thus, a closer examination or documented information about scheduling changes from organizations to minimize recall bias in a future study may explain work and SWB. A recent Swiss study by Fekete et al. (2020) in older adults with functional limitations because of spinal cord injury found that being engaged in volunteer but not paid work (p = 0.053) was associated with increased well-being. However, the combination of volunteer and/or paid work in the same group significantly increased well-being and decreased the odds of depression. Our results were similar to the Swiss study where volunteer work and a combination of volunteer and/or paid work (latter results not reported) significantly increased SWB, although 75% of our sample was physically active and most participated in some type of social activities.

Three types of activities—specifically, volunteer work, social participation, and physical activity—were significantly related to SWB of older adults after 1-year follow up. These results are similar to studies conducted among older adults from Europe and the United States, particularly in areas related to happiness and life satisfaction (Binder & Freytag, 2013; Borgonovi, 2008; Vozikaki et al., 2017). Our findings on physical activity are comparable to those of longitudinal studies that used self-reported subjective and objective wrist-worn physical activity measures and found that older adults who were physically active had significantly increased SWB (Ku et al., 2016; Lukaschek et al., 2017).

During retirement, older adults may compensate free time with productive activities that improve their subjective health (Anxo et al., 2019; McDonough et al., 2017) and cognitive performance (Lee et al., 2019) but not SWB. One example is the caregiving role of older adults, in which our study did not find any relationship. Although providing care to a family member or close friend is a productive activity that can provide caregivers with positive emotions or sense of accomplishment, caregiving may also add burden and decrease SWB (Li et al., 2017) or not contribute to SWB changes over time (Wahrendorf & Siegrist, 2010). Consequently, a close examination of these productive activities on SWB informs stakeholders, such as families, community organizers, and religious leaders, on ways to promote and maintain activities among older adults or use these activities as strategies to mitigate negative effects that may result from caregiving in late life, social isolation, or physical inactivity, among others. Although the study measured SWB as a unidimensional construct, it is evident in the SWB literature that productive activities do not equally influence hedonic, eudaimonic, and evaluative types of SWB. From a provider standpoint in health care or in the community, the latter calls for an evaluation of the different aspects of SWB (e.g., life satisfaction, meaningful life, happiness) older adults find important in late life, and consequently, tailor services and recommendations (e.g., go out, visit family or friends, attend religious services, walk, volunteer if capable, enroll in community programs) to support SWB.

Strengths and Limitations

The current study has a number of strengths and limitations. Strengths are related to the use of population data with complex survey techniques that enhance the representation of U.S. Medicare beneficiary older adults living in community and residential non-nursing home settings. The study was guided by the activity theory of aging and integrated productive activities that are social and economic in nature. It also controlled for a literature-driven set of explanatory variables, although the risk for unobserved characteristics that may have influenced the true relationships between productive activities and SWB may still exist. There are limitations related to the use of secondary data as well. Certain concepts, such as caregiving or fatigue, were measured by single dichotomous items that are generally less informative and may raise concerns for construct validity. The NHATS does not have any measure of evaluative SWB that may further help in understanding SWB experiences in relation to productive activities among older adults. Moreover, the study could not differentiate between voluntary and involuntary decisions related to work and retirement and time spent in retirement that may influence future SWB.


The current study demonstrated the positive nature of certain productive activities on SWB after 1-year follow up in community-dwelling older adults. These activities have social features, are person-driven, and more feasible to engage in than seeking paid work activity. As older adults live longer, it remains important to facilitate and encourage the practice of engaged productive activities within family and community circles to promote SWB. On the other hand, the relationship between postponed retirement and SWB is complex and is influenced by myriad personal factors, labor market and economic conditions, retirement pathways, and social security pensions. Although our study found no significant relationship between paid work and future SWB, indeed, this result is more favorable than an inverse significant relationship where many older adults have to continue with work. In future research, one recommendation is to explore and better understand the nature of the longitudinal relationships between paid work activity and work characteristics, productive activities, and SWB in the older adult population. Another recommendation is to test further the unidimensional measure of SWB among older adults and evaluate to what extent the results of productive activities change when compared to multidimensional SWB measures. These findings will help individuals engage in productive activities they find meaningful in later life and for community-level programs to initiate or restructure available activities to promote SWB.


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Sociodemographic and Health Characteristics of Older Adults

Characteristic% [95% CI]
Age (years)
  65 to 6942.84 [41.09, 44.61]
  70 to 7424.32 [22.75, 25.96]
  75 to 7916.30 [15.29, 17.35]
  80 to 849.56 [8.61, 10.61]
  ≥856.98 [6.37, 7.65]
Male45.07 [43.02, 47.14]
  White80.53 [77.64, 83.14]
  Black8.20 [7.15, 9.39]
  Other11.27 [8.90, 14.18]
  Less than high school14.84 [13.11, 16.75]
  High school32.42 [30.00, 34.93]
  Some college22.77 [20.65, 25.03]
  College or higher29.97 [26.86, 33.27]
Married or has a partner59.25 [56.96, 61.49]
Income in 2015 ($)b
  1st quartile19.83 [18.04, 21.75]
  2nd quartile22.03 [20.26, 23.89]
  3rd quartile26.49 [24.43, 28.65]
  4th quartile31.67 [28.81, 34.67]
Depressive symptomsa
  No89.29 [87.91, 90.53]
  Yes10.71 [9.47, 12.09]
Insomnia symptomsa
  No symptoms43.24 [41.18, 45.32]
  One symptom28.83 [26.79, 30.96]
  Two symptoms27.93 [26.16, 29.78]
Fatiguea (yes)40.34 [38.13, 42.58]
Memory recall
  No impairment94.26 [93.34, 95.06]
  Impairment (score ≤3)5.74 [4.94, 6.66]
Mean [95% CI]
Multimorbidity2.25 [2.19, 2.31]
Body mass index (kg/m2)a28.59 [28.36, 28.83]

Different Types of Engaged Activities and Subjective Well-Being (SWB) in Older Adults

Characteristic% [95% CI]
Paid worka
  Retired, not working79.03 [76.85, 81.05]
  Yes20.97 [18.95, 23.15]
Volunteer worka
  No71.11 [68.95, 73.18]
  Yes28.89 [26.82, 31.05]
Social engagement activity
  0 to 111.83 [10.33, 13.52]
  2 to 327.78 [25.90, 29.73]
  460.39 [58.42, 62.33]
Caregiving activitya
  No76.82 [74.66, 78.86]
  Yes23.18 [21.14, 25.34]
Online social activity
  No66.48 [64.58, 68.32]
  Yes33.52 [31.68, 35.42]
Physical activity
  Yes74.58 [72.74, 76.33]
  No25.42 [23.67, 27.26]
Mean [95% CI]
SWB–2015a17.52 [17.41, 17.64]
SWB–201617.10 [16.96, 17.24]

Relationships Between Engaged Activities and Subjective Well-Being (SWB) in Older Adults at 1-Year Follow Up

ParameterUnadjusted ModelModel 1Model 2Model 3Model 4
ß [95% CI]p Valueß [95% CI]p Valueß [95% CI]p Valueß [95% CI]p Valueß [95% CI]p Value
Paid work (yes)0.88 [0.61, 1.16]<0.0010.70 [0.41, 0.99]<0.0010.19 [–0.07, 0.45]0.1540.23 [–0.03, 0.48]0.0790.16 [–0.10, 0.42]0.214
Volunteer work (yes)1.14 [0.84, 1.43]<0.0010.65 [0.35, 0.95]<0.0010.45 [0.16, 0.75]0.0030.50 [0.21, 0.79]0.0010.29 [0.05, 0.54]0.020
Social participation activity
  0 to 1RefRefRefRefRef
  2 to 31.11 [0.54, 1.68]<0.0010.85 [0.27, 1.43]0.0050.58 [0.10, 1.06]0.0190.71 [0.23, 1.20]0.0050.55 [0.14, 0.97]0.010
  41.99 [1.47, 2.51]<0.0011.42 [0.88, 1.97]<0.0010.94 [0.46, 1.43]<0.0011.07 [0.57, 1.57]<0.0010.73 [0.31, 1.15]0.001
Caregiving activity (yes)0.20 [–0.09, 0.48]0.1820.04 [–0.23, 0.32]0.752
Online social activity (yes)0.12 [–0.12, 0.37]0.326
Physical activity (yes)1.42 [1.08, 1.76]<0.0011.06 [0.72, 1.40]<0.0010.46 [0.15, 0.77]0.0050.45 [0.14, 0.76]0.0050.34 [0.06, 0.61]0.021
SWB in tertiles at 2015
  2nd2.83 [2.56, 3.10]<0.0012.00 [1.72, 2.27]<0.001
  3rd4.32 [4.10, 4.54]<0.0013.31 [3.04, 3.58]<0.001

Dr. Sagherian is Assistant Professor, and Ms. Crawford is Doctoral Student, College of Nursing, The University of Tennessee, Knoxville, Tennessee; Dr. Rose is Professor and Director, Center for Healthy Aging, Self-Management and Complex Care, Ohio State University, Columbus, Ohio; Dr. Zhu is Associate Professor and Statistician, School of Nursing, University of Maryland, Baltimore, Maryland; and Dr. Byon is Assistant Professor, School of Nursing, University of Virginia, Charlottesville, Virginia.

The authors have disclosed no potential conflicts of interest, financial or otherwise. The National Health and Aging Trends Survey is sponsored by the National Institute on Aging (U01AG032947) through a cooperative agreement with the Johns Hopkins Bloomberg School of Public Health. The funding agency had no role in this secondary data analysis project.

Address correspondence to Knar Sagherian, PhD, RN, Assistant Professor, College of Nursing, The University of Tennessee, 1200 Volunteer Boulevard, Knoxville, TN 37996; email:

Received: April 22, 2020
Accepted: August 14, 2020
Posted Online: December 14, 2020


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