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. 2025 Apr 2;74(4):250–257. doi: 10.1097/NNR.0000000000000823

Behavioral and Functional Adaptation to Chronic Stress in Older Adults

Wan-chin Kuo 1,2,3,4,5, Karl P Hummel 1,2,3,4,5, Roger L Brown 1,2,3,4,5, Katherine Mead 1,2,3,4,5, Daniel J Liebzeit 1,2,3,4,5
PMCID: PMC12188819  PMID: 40203838

Abstract

Background

The wear and tear from chronic stress exposure has been linked to premature aging through allostatic load; however, it is unclear how chronic stress exposure affects physical functioning and physical activity in older adults.

Objectives

The study aims were to examine the behavioral and functional adaptation to chronic stress in older adults and its mediational pathways.

Methods

Data from the Health and Retirement Study 2016 and 2020 (N = 3075, mean age 66 years) were analyzed. Chronic and perceived stress exposure was quantified using Troxel’s Chronic Stressors Scale and Cohen’s Perceived Stress Scale. Physical activity was quantified using self-reported questionnaires, including light, moderate, and vigorous physical activity. Physical functioning was operated as a latent construct with four perceived physical limitations (i.e., difficulty in movement, hand strength, shortness of breath, and balance). The cross-sectional data were analyzed using latent regression analysis. The longitudinal data were analyzed using serial mediation based on MacKinnon’s bias-corrected bootstrap confidence intervals.

Results

Cross-sectionally, psychological stress, as a latent construct indicated by stress exposure and stress perception, explained more variances in perceived physical limitation than physical activity. Longitudinally, perceived stress and physical activity mediated the relationship between chronic stress exposure and perceived physical limitation with significant indirect effects. Furthermore, perceived physical limitation suppressed the effect of chronic stress exposure on physical activity levels. The effects of mediation and suppression remained significant after the adjustment for age, gender, years of education, race, number of comorbidities, working status, and marital status.

Discussion

The promotion of physical activity and physical functioning in older adults might not achieve the optimal outcome if the program design overlooks the target population’s chronic stress process and functional limitations.

Key Words: chronic stressor, mobility limitation, older adults, physical activity, physical function, perceived stress, serial mediation

Physical function, commonly known as the ability to perform physical tasks, is the essential physical state that enables an individual to complete regular, daily activities that require body movement, muscle contraction, and neuromotor coordination (Palmer et al., 2024). Physical limitation is manifested by the recurrent or progressive deterioration of the ability to produce body movement (e.g., walking, climbing stairs, or lifting objects), maintain physical positions (e.g., sitting, kneeling, or stooping), and perform physical transfers (e.g., getting in or out of a chair; Palmer et al., 2024). In contrast, perceived physical limitation is a subjective evaluation of one’s own capacities or constraints in performing daily activities or body movements. A medical diagnosis does not solely determine this perception but is also influenced by psychosocial factors, fatigue, pain, past experiences, and self-efficacy (Bean et al., 2011).

According to the recent AARP Medicare Supplement Survey, more than 35% of adults aged 65 and older were affected by moderate to severe physical limitations (Freiberger et al., 2020). Regular physical activity has been shown to improve physical function in older adults and being more active at a younger age results in better physical function later in life (García-Hermoso et al., 2020). However, the majority of middle-aged and older adults do not get adequate amounts of physical activity. According to the national surveillance with self-reported physical activity levels, only 14% of adults aged 65 and older met current physical activity recommendations (Hyde et al., 2021). Objective assessment with accelerometers showed that less than 2.5% of older adults in the United States met the recommended physical activity levels (Giné-Garriga et al., 2020).

Age-related loss in skeletal muscle mass and neuromotor performance contributes to the decline in physical functioning in older adults (Lee et al., 2024). The execution of daily activities and motor tasks requires skeletal muscle contractile activities, which are dictated by the mitochondria networks to provide proper supply and distribution of adenosine triphosphate within skeletal muscle cells (Huertas et al., 2019). While such declines are a natural part of aging, the rate of functional deterioration varies significantly among individuals due to a combination of chronic conditions, genetic predispositions, and environmental, behavioral, and psychosocial factors (Noguchi-Watanabe et al., 2024). The Allostatic Load Framework provides theoretical support to explain how chronic stress exposures cumulatively accelerate cellular aging and induce the molecular recalibrations of mitochondria networks through the hypothalamic–pituitary–adrenal axis hyperactivity (Epel et al., 2018). Consequently, cumulative stress activates pro-inflammatory pathways, including the release of cytokines such as interleukin-6 and tumor necrosis factor-alpha, which impair mitochondrial function, accelerate skeletal muscle degradation, and further exacerbate functional decline (Zhang & Dhalla, 2024).

In addition to the allostatic load cumulated from the physiological pathways, emerging evidence indicates that chronic stress exposures induce behavioral adaptation by shifting from a goal-directed cognitive system to a habitual responding system (Meier et al., 2022). To preserve cognitive capacity for stressful demands, daily health behaviors (e.g., physical activity and healthy diet), if not deliberately self-managed, are often reconciled as self-care routines regulated by the habitual responding system. However, the habitual responding system is noticeably susceptible to environmental and contextual cues, repetition, and conditional rewards. Individuals living in stressful contexts are more likely to experience health disparities and suffer from environmental injustice, where contextual cues are often less healthy, stressors tend to co-occur, and momentary and short-term rewards are distortedly tempting (Michaelsen & Esch, 2021).

Although the Allostatic Load Framework explains how cascading allostatic load—synergistically built up through behavioral and physiological responses—could accelerate the aging process (Epel et al., 2018), many alternative directional pathways have not been studied. First, acute deterioration in health conditions can serve as a chronic stressor, such as the exacerbation of comorbidities or hospitalization, interfering with the dual (physiological and behavioral) pathways of stress. For instance, recent research highlights that personal health issues are among the most prevalent stressors for older adults and frequently coincide with family health challenges, which synergistically influence insomnia symptoms (Kuo, Ersig, et al., 2023). Second, although the crosstalk between behavioral and functional adaptations to chronic stress in older adults has been explored in qualitative studies (Liebzeit et al., 2020), it has not been fully examined in longitudinal studies. Theoretically, chronic stress exposure could impede physical activity, leading to functional decline (Supplemental Digital Content [http://links.lww.com/NRES/A560] 1 Model A). Yet, practically, the functional decline with chronic stress exposures might, in turn, limit older adults’ physical activity levels (SDC [http://links.lww.com/NRES/A560] 1 Model B).

Although the COVID-19 pandemic increased perceived stress across the nation, there remains limited understanding of how chronic stress proliferated during this period and its subsequent effect on physical activity and physical functioning in the aging population. The distinctive cohort design of the Health and Retirement Study (HRS; 2016–2020) provides a valuable opportunity to explore stress proliferation both before and during the COVID-19 pandemic and examine how chronic stress over time influences behavioral and functional adaptation in an aging population transitioning from midlife to later life. This study aimed to test two key hypotheses:

Hypothesis 1: Perceived stress and physical activity mediated the effect of chronic stress proliferation on perceived physical limitation in older adults (SDC 1 [http://links.lww.com/NRES/A560] Model A).

Hypothesis 2: Perceived stress and perceived physical limitation mediated the effect of chronic stress proliferation on physical activity in older adults (SDC 1 [http://links.lww.com/NRES/A560] Model B).

METHODS

Design, Setting, and Sample

A longitudinal analysis was performed using the HRS data. The HRS is a national longitudinal survey of more than 37,000 individuals over the age of 50 in 23,000 households in the United States (Sonnega et al., 2014). Since 1992, socioeconomic, psychological, and health data were assessed in this core sample approximately every 2 years. In 2006, half the core sample was randomly assigned to enhanced face-to-face interviews with physical and biological measures and a mail-back psychosocial questionnaire. Data from the enhanced face-to-face interviews are available for every wave on half of the core and full samples every 4 years. HRS employs a national area probability sampling method to represent U.S. households, with additional oversampling of Black and Hispanic populations, as well as residents of Florida (Heeringa & Connor, 1995). The majority of the HRS sample population is either approaching retirement or already retired, but it also includes individuals who are employed, unemployed, or have never worked outside the home (Heeringa & Connor, 1995). Details about the HRS design are described elsewhere (Sonnega et al., 2014).

This longitudinal data analysis was based on the HRS 2016–2020 data. Definitions of which ages define “senior citizens” are based on different legal, social, and health contexts (e.g., Social Security benefits, senior housing, retirement saving plans, or Medicare). To capture the early effect of upstream stress exposures on physical activity and physical functioning in the aging process, the current data analysis included respondents who were 50 or older in 2016 as the baseline. The inclusion criteria were: (a) age of 50 or older at baseline, (b) never been diagnosed with cognitive impairment (including dementia or Alzheimer’s disease), and (c) did not have missing data in chronic stressors or perceived physical functioning. Participants diagnosed with cognitive impairment were not included in the current analysis due to the pathological and treatment-associated concomitant effects on stress perception, physical activity, and physical functioning. In total, 3,075 respondents were included in the current data analysis. The flow chart of the final sample is presented in SDC 2 (http://links.lww.com/NRES/A560).

The HRS was reviewed and approved by the University of Michigan’s Health Sciences Institutional Review Board (IRB). All participants read a confidentiality statement and gave oral or implied consent by agreeing to participate in the study. The local university’s IRB approved this secondary data analysis with an exemption from full IRB review.

Primary Exposure and Outcome Variables

Chronic Stress Exposure

Chronic stress exposure was assessed using Troxel’s Chronic Stressor Scale (CSS-8), covering chronic stressors in eight areas of life: (a) self-health problems, (b) family health problems, (d) alcohol or drug use in family members, (e) difficulties at work, (f) financial strain, (g) housing problems, (h) problems in a close relationship, and (i) caregiving stress (Troxel et al., 2003). Chronic stress exposure is defined as the subjective experience of chronic stressors that older adults encounter daily. Respondents evaluated the occurrence of each chronic stressor and subjective upset associated with each stressor during the past 12 months using a Likert-type scale (1 = did not occur, 2 = not upsetting; 3 = somewhat upsetting; 4 = very upsetting). For Item 4 in CSS-8 (i.e., difficulties at work), respondents were coded as “did not occur” if they were not currently working for pay and reported missing values in difficulties at work. The composite score was calculated as the summation of the scores for the eight items, ranging from 8 to 32. The higher scores indicate higher degrees of chronic stress exposure. Because the eight stressors represent eight different areas of life, they are not intended to have a high degree of internal consistency. Prior evidence indicates acceptable reliability of CSS-8 with Cronbach’s α of 0.66 and good predictive validity of CSS-8 for insomnia symptoms (Kuo, Ersig, et al., 2023).

Perceived Physical Limitation

Perceived physical limitation was operationalized as a latent construct with four indicators based on self-report questionnaires, including movement, hand strength, shortness of breath, and balance. Initially developed by Nagi (1976), the 12-item functional difficulty scale assesses the subjective difficulty of physical performance in 12 tasks related to movement: (a) walking several blocks, (b) jogging 1 mile, (c) walking 1 block, (d) sitting 2 hours, (e) getting up from a chair, (f) climbing stairs, (g) climbing one flight of stairs, (h) stooping, (i) reaching arms, (j) pull/push large objects, (k) lifting weights, and (l) picking up a dime (Nagi, 1976). The composite score was calculated as the total number of difficulties performing these 12 tasks. The higher score indicates higher perceived difficulty in movement. The hand strength, shortness of breath, and balance were evaluated using three items: (a) “How often do you have difficulty with balance?” (b) How would you rate your hand strength?” and (c) “How often do you become short of breath while awake.” The scores were coded or reverse-coded to allow for interpretation, with higher scores indicating higher perceived physical limitations. Cronbach’s alpha of the 12-item functional difficulty scale was 0.80 in community-dwelling older adults (Dong et al., 2014).

Mediating Variables

Perceived Stress

Perceived stress was assessed using Cohen’s Perceived Stress Scale (PSS-10) with a Likert-type scale (0 = never, 1 = almost never, 2 = sometimes, 3 = fairly often, 4 = very often) (Cohen et al., 1994). Perceived stress was defined as the subjective appraisal of general feelings of unpredictability, uncontrollability, irritation, or overload toward life demands. PSS-10 is an event-independent measure asking respondents how often the stressful sensations (e.g., unpredictability, uncontrollability, irritation, or overload) occurred in the past month (Cohen et al., 1994). Items 4, 5, 7, and 8 were reverse-coded, and the composite score was calculated as the summation of the scores for the 10 items, ranging from 0 to 40. The higher scores indicate higher degrees of general perceived stress. The PSS-10 demonstrated excellent reliability with Cronbach’s α of 0.852 in the current sample, consistent with prior reliability assessments of the PSS-10 in the U.S. population (Cohen et al., 1994). Missing values in items of the PSS-10 were checked for missing patterns and handled with multiple imputations.

Physical Activity

Physical activity was assessed with three items, asking about the frequency of vigorous physical activity (VPA), moderate physical activity (MPA), and light physical activity (LPA) that the participants performed in their day-to-day lives. VPA was defined as sports or activities that are vigorous in intensity, such as running or jogging, swimming, cycling, aerobics or gym workout, tennis, or digging with a spade or shovel. MPA was defined as sports or activities that are moderately energetic, such as gardening, cleaning the car, walking at a moderate pace, dancing, and floor or stretching exercises. LPA was defined as mildly energetic activities, such as vacuuming, laundry, or home repairs. Responses were rated on a four-point Likert-type scale: (a) more than once a week or every day, (b) once a week, (c) one to three times a month, or (d) hardly ever or never. Scores were reverse-coded, with higher scores indicating higher degrees of physical activity engagement. Recent evidence has shown its construct validity for chronic inflammation and physical functioning in older adults with confirmatory factor analysis (Hlebichuk et al., 2023). Missing values in VPA, MPA, and LPA were checked for missing patterns and handled with multiple imputations.

Covariates

Age, gender, years of education, and race were assumed as time-invariant covariates. The number of comorbidities, working status, and marital status were time-variant covariates and were based on the statuses reported during the COVID-19 pandemic. Specifically, the number of comorbidities was calculated as the summation of existing chronic conditions reported during the COVID-19 pandemic, including hypertension, diabetes, cancer, lung diseases, cardiovascular diseases, stroke, depression, and arthritis. Current work status was a binary variable indicating whether the respondents did any work for pay (including part-time and full-time jobs) during the COVID-19 pandemic. Respondents who self-identified as retirees or housekeepers were categorized as not currently working for pay.

Analysis

The sample size requirement was estimated based on the recommended ratio of cases to free parameters (N:q approach) of 10:1 to 20:1 (Kyriazos, 2018). The hypothesized serial mediation model includes 13 fixed and 27 free parameters, with 40 parameters in total. Based on the 20:1 ratio, the minimum sample size required is estimated at 540. Therefore, the current sample size of 3,075 is sufficient for hypothesis testing.

As shown in SDC 3 (http://links.lww.com/NRES/A560), missing values were identified in perceived stress items, physical activity items, race, ethnicity, education, and work status. The diagnosis of missing patterns with Little’s test for Missing Completely at Random rejected the null hypothesis (X2 = 852.66; p = .002), indicating that the missing values were not Missing Completely at Random (Little, 1988). Hence, missing values were imputed under the assumption of missing at random, where missingness in the perceived stress, physical activity, and covariates were not due to chronic stress exposure or physical functioning statuses. Multiple imputation was performed using the Monte Carlo Markov Chain method based on 100 iterations with five imputed data sets (Asparouhov & Muthén, 2010).

The cross-sectional associations among psychological stress, physical activity, and perceived physical limitation during the COVID-19 pandemic were examined using the latent regression model with maximum likelihood method. The univariate skewness and kurtosis values for each outcome variable fall within the range of −2 to +2, indicating acceptable distributions of outcome variables. The multivariate kurtosis for the cross-sectional data with the latent regression model is 8.644, which falls below the threshold of 10, indicating an acceptable level of normality with a large sample size. R2 was used to examine the percentages of variances in physical activity and perceived physical limitations that were explained by the latent construct of psychological stress indicated by stress exposure and stress perception. The goodness-of-fit was evaluated based on the following indices and cutoff: comparative fit index (CFI) ≥ .95, the Tucker–Lewis Index (TLI) ≥ .95, the root mean square error of approximation (RMSEA) ≤ .05, and the standardized root mean square residual (SRMR) index ≤ .05 (Byrne, 2016).

To examine the mediation effects of physical activity in the association between chronic stress exposure and perceived physical limitation, we used MacKinnon et al.’s (2004) bias-corrected confidence intervals (CI) to examine the direct, indirect, and total effects. The multivariate kurtosis for the longitudinal data with the serial mediation model is 13.202, indicating a deviation from the normality assumption. While the larger sample size (N = 3,075) mitigates the effect of kurtosis through the central limit theorem, extreme values could still influence the results. We applied bias-corrected bootstrap CI in the serial mediation model to address this, ensuring robust parameter estimates (Collier, 2020). MacKinnon’s product of coefficients approach with resampling (bootstrapping) was used for the serial mediation analysis because it addresses several limitations of the causal steps method, including (a) requiring a smaller sample size to detect a mediation effect and (b) allowing researchers to identify significant indirect effects in the absence of a total effect—especially when several mediating paths have opposite signs that cancel each other out (MacKinnon et al., 2004). The direct, indirect, and total effects were estimated using bias-corrected bootstrap CI (bootstrap = 200); indirect effects were considered significant if the 95% CI did not contain 0 (Zhao et al., 2010). The CFI, TLI, RMSEA, and SRMR were used as the goodness-of-fit indices to ensure the estimated model is reasonably consistent with the current sample. Statistical analyses were performed using IBM Amos 29 (Byrne, 2016). All reported p-values were two-tailed, with p-values less than 0.05 considered significant.

RESULTS

Sample Characteristics

A total of 3,075 participants were included in the current study. As described in Table 1, the mean age was 66 (SD = 9.5), 1,223 (39.8%) participants were men, 2,289 (74.4%) participants were White, and 356 (11.6%) participants were Hispanic. About one-third (33%) of the participants were working for pay during the COVID-19 pandemic. More than two-thirds (69.9%) of the participants reported at least two chronic conditions.

TABLE 1.

Descriptive Results of Sample Characteristics (N = 3,075)

Frequency (or mean) % (or SD)
Age, mean (SD) 66.0 9.5
Male, N (%) 1,223 39.8
Race, N (%)
 White 2,289 74.4
 Black 535 17.4
 Othera 251 8.2
Hispanic, N (%) 356 11.6
Working for pay, N (%) 1,016 33.0
Marital status, N (%)
 Married 1,760 57.2
 Separated/divorced 551 17.9
 Widowed 576 18.7
 Never married 180 5.9
 Other 8 0.3
Years of education, mean (SD) 13.5 2.8
Number of comorbidities, N (%)b
 None 298 9.7
 One 628 20.4
 Two 829 27.0
 Three 693 22.5
 Four or more 627 20.4
Chronic stressor 2016, mean (SD)c 12.7 3.9
Chronic stressor 2020, mean (SD)c 12.0 3.4
Perceived stress, mean (SD)d 11.9 6.6
VPA, N (%)
 Never 1,610 52.4
 One to three times per month 311 10.1
 Once per week 366 11.9
 More than once per week 788 25.6
MPA, N (%)
 Never 541 17.6
 One to three times per month 350 11.4
 Once per week 522 17.0
 More than once per week 1,662 54.0
LPA, N (%)
 Never 230 7.5
 One to three times per month 223 7.3
 Once per week 816 26.5
 More than once per week 1,806 58.7
Mobility difficulties, mean (SD)e 2.17 2.6
Hand strength, N (%)
 Very strong 538 17.5
 Somewhat strong 1,896 61.7
 Somewhat weak 558 18.1
 Very weak 83 2.7
Shortness of breath, N (%)
 Never 1,495 48.6
 Rarely 1,068 34.7
 Sometimes 409 13.3
 Often 103 3.3
Balance difficulty, N (%)
 Never 1,018 33.1
 Rarely 1,187 38.6
 Sometimes 668 21.7
 Often 202 6.6
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Note. SD = standard deviation; VPA = vigorous physical activity; MPA = moderate physical activity; LPA = light physical activity.

a Includes American Indian, Alaskan Native, Asian or Pacific Islander.

b Comorbidities include hypertension, diabetes, cancer, lung diseases, cardiovascular diseases, stroke, depression, and arthritis.

c Higher values indicate higher levels of chronic stress exposure (range: 8–32).

d Higher values indicate higher levels of perceived stress (range: 0–40).

e Higher values indicate higher levels of mobility difficulties (range: 0–12).

Cross-Sectional Latent Regression Analysis

The crude model of latent regression analysis (SDC 4 [http://links.lww.com/NRES/A560]) showed that psychological stress as a latent construct (indicated by chronic stress exposure and perceived stress) was significantly associated with physical activity (β = −0.38, R2 = .15) and perceived physical limitation (β = 0.54; R2 = .29). However, the crude model of latent regression analysis yielded poor model fit: CFI = 0.866; TLI = 0.807; RMSEA = 0.099, 90% CI [0.093, 0.105]; SRMR = 0.0998. After the adjustment of covariates, the latent regression model yielded an improved model fit: CFI = 0.902; TLI = 0.825; RMSEA = 0.066, 90% CI [0.062, 0.069]; SRMR = 0.046. As shown in Figure 1, the latent construct of psychological stress was significantly associated with physical activity (β = −0.29, R2 = .31) and perceived physical limitation (β = 0.40; R2 = .53), after the adjustment for age, gender, education, race, ethnicity, comorbidities, work status, and marital status.

FIGURE 1.

FIGURE 1

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Latent regression model of the relationships among the latent constructs of psychological stress, physical activity, and perceived difficulty in physical function during the COVID-19 pandemic with the adjustment of covariates.

Longitudinal Serial Mediation Analysis

Hypothesis 1: Perceived Stress and Physical Activity Mediated the Effect of Chronic Stress Proliferation on Perceived Physical Limitation in Older Adults

The serial mediation analysis confirmed the mediation effects of perceived stress and physical activity in the association between chronic stress exposure and perceived physical limitation. As shown in Table 2, perceived stress and physical activity mediated the relationship between chronic stress exposures and perceived physical limitation with significant indirect effect (β = 0.016; bias-corrected 95% CI = [0.013, 0.019]; p = .004). Model fit indexes for the unadjusted model showed an excellent model fit: CFI = 0.983; TLI = 0.973; RMSEA = 0.037, 90% CI [0.031, 0.043]; SRMR = 0.024. As illustrated in SDC 5 [http://links.lww.com/NRES/A560], chronic stress exposure in both 2016 and 2020 and perceived stress in 2020 explained only 6% of variances in physical activity (R2 = 0.06). Whereas chronic stress exposure in both 2016 and 2020, perceived stress in 2020, and physical activity in 2020 explained up to 52% of variances in perceived physical limitation (R2 = .52). The indirect, direct, and total effects remained significant after the adjustment of covariates, and the explained variances in physical activity and perceived physical limitation increased, with R2 of .27 and .63, respectively (Figure 2).

TABLE 2.

Bootstrap Bias-Corrected Confidence Interval for the Indirect, Direct, and Total Effects Derived From Hypothesis 1 (Model A: CSE16 → CSE20 → PS→PA→PPL) and Hypothesis 2 (Model B: CSE16 → CSE20 → PS→PPL→PA)

Unadjusted model Covariate-adjusted modela
β Bootstrap SE Bias-corrected 95% CI p β Bootstrap SE Bias-corrected 95% CI p
Hypothesis 1 (Model A): CSE16 → CSE20 → PS → PA → PPL
CSE16 → PPL
Indirect effect 0.016 0.002 [0.013, 0.019] .004 0.011 0.001 [0.008, 0.014] .005
Direct effect 0.013 0.002 [0.009, 0.018] .010 0.010 0.002 [0.006, 0.014] .009
Total effect 0.029 0.002 [0.024, 0.034] .011 0.021 0.002 [0.017, 0.025] .007
CSE20 → PPL
Indirect effect 0.011 0.002 [0.007, 0.015] .013 0.008 0.002 [0.005, 0.012] .009
Direct effect 0.006 0.003 [0.001, 0.012] .007 0.007 0.002 [0.003, 0.013] .005
Total effect 0.017 0.003 [0.012, 0.022] .009 0.016 0.002 [0.011, 0.020] .006
PS → PPL
Indirect effect 0.006 0.001 [0.004, 0.008] .011 0.003 0.001 [0.002, 0.005] .006
Direct effect 0.005 0.001 [0.003, 0.008] .013 0.004 0.001 [0.002, 0.007] .010
Total effect 0.011 0.001 [0.008, 0.014] .009 0.007 0.001 [0.005, 0.010] .007
Hypothesis 2 (Model B): CSE16 → CSE20 → PS → PPL → PA
CSE16 → PA
Indirect effect −0.052 0.005 [−0.061, −0.041] 0.014 −0.035 0.004 [−0.045, −0.028] .007
Direct effect 0.014 0.006 [0.004, 0.026] 0.012 0.010 0.005 [0.001, 0.020] .038
Total effect −0.038 0.005 [−0.047, −0.028] 0.008 −0.025 0.005 [−0.036, −0.018] .002
CSE20 → PA
Indirect effect −0.036 0.006 [−0.045, −0.026] 0.011 −0.030 0.005 [−0.039, −0.021] .007
Direct effect 0.010 0.007 [−0.003, 0.025] 0.161 0.005 0.007 [−0.008, 0.019] .420
Total effect −0.026 0.007 [−0.042, −0.013] 0.008 −0.025 0.007 [−0.037, −0.010] .011
PS → PA
Indirect effect −0.021 0.003 [−0.027, −0.015] 0.012 −0.012 0.002 [−0.017, −0.008] .014
Direct effect −0.004 0.003 [−0.011, 0.001] 0.170 −0.004 0.003 [−0.010, 0.002] .198
Total effect −0.025 0.003 [−0.034, −0.019] 0.009 −0.016 0.003 [−0.024, −0.011] .004
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Note. CSE = chronic stress exposure; PS = perceived stress; PA = physical activity; PPL = perceived physical limitation. Model fit indexes for the unadjusted model: CFI = 0.983; TLI = 0.973; RMSEA = 0.037, 90% CI [0.031, 0.043]; SRMR = 0.024; AIC = 197.203; BIC = 360.042.

Model fit indexes for the covariate-adjusted model: CFI = 0.954; TLI = 0.900; RMSEA = 0.050, 90% CI [0.046, 0.054]; SRMR = 0.028; AIC = 727.086; BIC = 1269.881.

a Age, gender, race, ethnicity, education, work status, marital status, and number of comorbidities were controlled as covariates.

FIGURE 2.

FIGURE 2

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The direct and indirect effects of chronic stress exposures on perceived physical limitation through perceived stress and physical activity. Serial mediation analysis with the adjustment of covariates. Note. CSE16 = chronic stress exposure in 2016; CSE20 = chronic stress exposure in 2020; PS=perceived stress; PA = physical activity; PPL = perceived physical limitation.

Hypothesis 2: Perceived Stress and Perceived Physical Limitation Mediated the Effect of Chronic Stress Proliferation on Physical Activity in Older Adults

As illustrated in SDC 6 (http://links.lww.com/NRES/A560), the mediation effects of perceived stress and perceived physical limitation in the association between chronic stress exposure and physical activity were also confirmed in the serial mediation analysis, yet with evidence of suppression effect. More specifically, as detailed in Table 2, the indirect effect of chronic stress exposure in 2016 on physical activity was significant (β = −0.052; bias-corrected 95% CI = [−0.061, −0.041]). However, the total effect (β = −0.038) was closer to zero than the indirect effect (β = −0.052), and the indirect (β = −0.052) and direct effects (β = 0.014) were presented with opposite signs. This coefficient pattern, as explained by MacKinnon et al. (2000), indicates the presence of a suppressor effect, where the direct and indirect effects cancel each other out, leading to a weaker total effect. The model remained significant after the adjustment of covariates. As illustrated in Figure 3, the effects of chronic stress exposures (both 2016 and 2020) on physical activity were mediated by perceived stress and perceived physical limitation after adjusting covariates. Chronic stress exposure in 2016 and 2020, as well as perceived stress, explained 47% of variances in perceived physical limitation (R2 = .47); chronic stress exposure in 2016 and 2020, perceived stress, and perceived physical limitation explained 50% of variances in physical activity (R2 = .50).

FIGURE 3.

FIGURE 3

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The direct and indirect effects of chronic stress exposures on physical activity through perceived stress and perceived physical limitation. Serial mediation analysis with the adjustment of covariates. Note. CSE16 = chronic stress exposure in 2016; CSE20 = chronic stress exposure in 2020; PS = perceived stress; PA = physical activity; PPL = perceived physical limitation.

DISCUSSION

In the United States, more than 35% of older adults experience physical limitations (Freiberger et al., 2020). Active living is a crucial indicator of healthy aging, whereby more benefits (e.g., metabolic and physical functioning) occur with physical activity performed on a regular basis to achieve physical activity recommendations (Eisenhauer et al., 2021). Although the general guidelines recommend at least 150 min of moderate-intensity aerobic activity or 75 min of vigorous-intensity aerobic activity and at least 2 days of muscle-strengthening activities per week, the guidelines also emphasize that any amount of exercise is better than being sedentary—even if health status hinders a person from achieving recommended goals (Lee et al., 2017). Three or more days per week of multicomponent physical activities that include balance, coordination, and strength training could significantly enhance physical functioning and reduce fall risks in older adults (U.S. Department of Health and Human Services, 2018). In current practice, individualized training plans start from physical assessment, goal setting, identification of barriers and solutions, and recommendations for activity type, frequency, and intensity (Lee et al., 2017). Our findings underscore the importance of tailoring older adults’ training plans based on the assessment of physical functioning when making training recommendations for older adults rather than providing general recommendations.

Despite the theoretical premises explaining the behavioral adaptation under chronic stress exposure, existing evidence examining the effect of stress exposure on physical activity in older adults is limited and inconsistent. For instance, recent studies have shown that older adults with financial stress were less likely to meet physical activity recommendations (Kuo, Bratzke, et al., 2023), while Ensel and Lin (2004) found no association between life stressors and physical activity levels in the aging population. More recently, de Oliveira et al. (2021) found that generic perceived stress in older adults was positively associated with sedentary time on weekends. Whereas Leger et al. (2023) found that older adults’ weekly time spent on physical activity or sedentary behavior was not associated with interpersonal stressors. Our latent regression analysis (Figure 1) indicates that psychological stress as a latent construct of stress exposure and perception was associated with lower levels of physical activity and higher degrees of perceived physical limitations, which is consistent with Stults-Kolehmainen & Sinha’s (2014) systematic review that adults experiencing chronic stress are less likely to be physically active. However, the interrelationships among older adults’ stress process, physical limitation, and physical activity remained unexplained without further mediation analysis.

As presented in Figures 2 and 3, when holistically examining the two responding pathways of chronic stress exposures (regardless of the behavior as mediator or physical limitation as mediator), we found no direct effect of chronic stress exposures in 2020 on physical activity but the indirect effect of chronic stress exposure in 2020 on physical activity through perceived stress was significant. In other words, individuals’ perceived stress mediates behavioral adaptation under chronic stress exposure. Without diving into the serial mediation analysis, if we prematurely conclude that chronic stress exposures and perceived stress play similar roles in physical activity based on our latent regression model (Figure 1), this would have been a wrong conclusion.

What makes the stress response more complex is the suppression effect identified in Model B, which examined the mediation role of perceived physical limitation in the stress–behavioral relationship. As shown in Table 2 (Model B), perceived physical limitation significantly mediated the effects of chronic stress exposure on physical activity; however, the direction of direct and indirect effects is opposite. In other words, older adults experiencing chronic stressors might plan to engage in physical activity for any reason (e.g., exercise is good for their health); still, their physical limitations might impede their ability to carry out physical activity plans or meet physical activity recommendations. Pearlin and other researchers in the field of social stress have provided empirical evidence of suppression effects within the stress process model (Avison et al., 2009), although suppression effects are not accounted for in the Allostatic Load Framework. Our findings address a gap in the Allostatic Load framework by explaining why older adults with chronic stress often struggle to fully meet physical activity recommendations and highlighting how clinicians and nurses can offer support to mitigate the stress-related effects on functional decline.

Chronic stressors come from various areas of life and role domains. Most chronic stressors do not have clear onsets or endpoints (Scott et al., 2015), and therefore, resource allocations and coping mechanisms to manage these chronic stressors are essential skills over the life course. Older adults cope with persistent problems in their lives with three types of coping mechanisms: (a) problem-focused, (b) emotion-focused, and (c) meaning-focused. Problem-focused coping often involves resource allocations and is used in stressors with greater control (Avison et al., 2009). In contrast, emotion-focused and meaning-focused coping mechanisms are often used in chronic difficulties when individuals have less control over, during which meanings or values are assigned to the roles that involve role domain strains (e.g., job-related stress or caregiving stress); meanwhile, emotions might be channeled through journaling, social support, or close conversations (Thoits, 2010). However, a well-noted type of coping mechanism is compensatory coping, whereby adults engage in other behaviors or activities (e.g., social engagement or physical activities) to help them counterbalance the psychological cost of stressful life demands they experience (Liebzeit et al., 2022; Thoits, 2010). Although physical activity cannot resolve the stressor itself, it has been shown to improve adults’ emotional resilience to stress (Bernstein & McNally, 2018; Stults-Kolehmainen & Sinha, 2014).

Limitations

This secondary analysis has several limitations. First, findings from this study should be interpreted under the context of our longitudinal analysis with HRS 2016–2020, during which the COVID-19 pandemic struck the nation, posing threats to our findings’ ecological and temporal validity. Evidence has indicated that the COVID-19 pandemic created a unique macro-destruction and magnified health disparities in the aging population. Nonetheless, this limitation offers future study opportunities, especially as subsequent HRS survey waves become available. Second, although the stress process was captured through repeated assessments of chronic stress exposure in 2016 and 2020, the generalizability of findings to older adults at the national and global levels living in various social contexts may be difficult to ascertain with the snapshot approach at two time points. Third, due to the COVID-19 pandemic, physical measures requiring in-person contact were not available in HRS 2020. Hence, physical activities and functioning in the current study were quantified based on subjective measures without performance-based assessments, such as the usual gait speed test, semi-tandem hold balance test, handgrip strength test, or wearable devices (e.g., actimetry sensors for gross motor activity). Despite the uncontrolled discrepancy between perceived physical limitations and actual physical functioning in the current study, previous research by Bean et al. (2011) suggests that subjective measures of physical limitations not only capture physical attributes but also encompass other health and psychosocial factors, thus providing a more complex view of physical functioning. Finally, the biomarker data from the HRS were not utilized in the current analysis, limiting the ability to explore the physiological pathways of chronic stress and its behavioral interactions within the Allostatic Load Framework (Epel et al., 2018). Future research leveraging HRS biomarkers is strongly recommended to elucidate the complex physiological and behavioral mechanisms of chronic stress in aging populations.

CONCLUSION

This study reveals a suppression effect of perceived physical limitations in the stress–physical activity relationship, a phenomenon not addressed by the Allostatic Load Framework. This effect helps explain why older adults with chronic stress often encounter barriers to meeting physical activity recommendations. While the mediation and suppression analysis might overlook the complexity of the stress process and functional decline in aging populations, it highlights the role of stress proliferation, perceived stress, and physical limitations in older adults’ physical activity behaviors. The promotion of physical activity and physical functioning in older adults might not achieve the optimal outcome if the program design overlooks the target population’s chronic stress process and functional limitations.

Footnotes

Acknowledgment: The Health and Retirement Study is sponsored by the National Institute on Aging (grant number U01AG009740) and is conducted by the University of Michigan. This work was supported by the University of Wisconsin-Madison, Vice Chancellor for Research and Graduate Education grant. The authors would like to thank the participants who participated in the Health and Retirement Study. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The authors have no conflicts of interest to report.

Ethical Conduct of Research: The Health and Retirement Study was reviewed and approved by the University of Michigan's Health Sciences Institutional Review Board (IRB). All participants read a confidentiality statement and gave oral or implied consent by agreeing to participate in the study. This secondary data analysis was approved by the University of Wisconsin-Madison’s IRB with an exemption from full IRB review.

Clinical Trial Registration: N/A

Data Availability: Health and Retirement Study data were collected, managed, and maintained by the University of Michigan with funding from the National Institute on Aging (grant number U01AG009740), Ann Arbor, MI. Program code supporting the findings of this study are available from the corresponding author on request. All users who analyze Health and Retirement Study data should follow the Health and Retirement Study Data Access User Agreement.

Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal’s Web site (www.nursingresearchonline.com).

Contributor Information

Karl P. Hummel, Email: karlhummel52@gmail.com.

Roger L. Brown, Email: roger.brown@wisc.edu.

Katherine Mead, Email: meadx036@gmail.com.

Daniel J. Liebzeit, Email: daniel-liebzeit@uiowa.edu.

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