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. 2024 Mar 22;79(6):gbae040. doi: 10.1093/geronb/gbae040

Prior Incarceration and Performance on Immediate and Delayed Verbal Recall Tests: Results From National Longitudinal Study of Adolescent to Adult Health—Parent Study

Alexander Testa 1,✉, Dylan B Jackson 2, Meghan Novisky 3, Kyle T Ganson 4, Jason M Nagata 5, Jack Tsai 6,7
Editor: Kenzie Latham-Mintus
PMCID: PMC11101758  PMID: 38518200

Abstract

Objectives

This study aimed to investigate the cognitive functioning of formerly incarcerated older adults compared to their never-incarcerated counterparts, focusing on immediate and delayed verbal recall.

Methods

Data are from 2,003 respondents who participated in the National Longitudinal Study of Adolescent to Adult Health—Parent Study (AHPS; ages 47–82, mean age 62). AHPS participants were administered word recall memory exercises to the parent respondent from the Rey Auditory-Verbal administered Learning Test, including (a) 90-s (immediate or short-term verbal memory), (b) 60-s recall tests (delayed or long-term verbal memory), and (c) combined word recall on the 90-s and 60-s tests.

Results

Adjusting for control variables, respondents who reported prior incarceration had a lower rate of verbal recall on the combined word recall (incidence risk ratio [IRR] = 0.915, 95% confidence interval [CI] = 0.840, 0.997) and immediate word recall (IRR = 0.902, 95% CI = 0.817, 0.996). When restricting the sample to respondents over age 60, prior incarceration was associated with lower combined word recall (IRR = 0.847, 95% CI = 0.752, 0.954), immediate word recall (IRR = 0.857, 95% CI = 0.762, 0.963), and delayed word recall (IRR = 0.834, 95% CI = 0.713, 0.974).

Discussion

This study underscores the adverse impact of prior incarceration on cognitive functioning in the older adult population, emphasizing the need for targeted interventions and support for formerly incarcerated older adults. The results reinforce the importance of addressing the long-term consequences of incarceration, especially as individuals enter older adulthood.

Keywords: Cognition, Incarceration, Memory, Word recall

Between the 1970s and late 2000s, the United States incarceration rate increased by approximately 500%, leading to exceptional levels of incarceration relative to the rest of the world (Travis et al., 2014) and vast racial disparities reflected by disproportionately high incarceration rates of Black, Hispanic, and Native American persons (Nellis, 2021; Pettit & Gutierrez, 2018). During this period, there were substantial increases in the number of women who experienced incarceration (Heimer et al., 2023) and an increase in older currently and formerly incarcerated people (Kim & Peterson, 2016). The massive change in the size and scope of incarceration has significant implications for the health of those who have experienced incarceration (Massoglia & Remster, 2019; Wildeman & Wang, 2017). However, much of the existing research on the health consequences of incarceration focuses on young and middle-aged adults, with far fewer studies examining the long-term impacts of incarceration for older adult populations (Garcia-Grossman et al., 2023; Latham-Mintus et al., 2022; Tanksley et al., 2023; Testa et al., 2023).

Incarceration is a highly stressful life event that can negatively affect healthy aging and cognition. The stress process model posits that stressors, events, and disruptions to one’s life experienced among vulnerable populations can have meaningful health consequences for several reasons (Pearlin, 2010; Pearlin et al., 1981; Thoits, 2010). First, the stress process model highlights inequality in exposure to stressors, with exposure to incarceration concentrated among minoritized populations and those of lower socioeconomic status (Nellis, 2021; Pettit & Gutierrez, 2018; Wakefield & Uggen, 2010). Second, incarceration is a stressor that can proliferate across people and generations, and thus not only harms the well-being of the person directly exposed to incarceration but also negatively affects the well-being of adult family members (Turney, 2021), children (Wildeman et al., 2018), and communities (Kajeepeta et al., 2020). Finally, the primary stressor of incarceration can lead to secondary stressors such as economic hardship (Harper et al., 2021; Maroto, 2015), fractured family relationships and social ties (Rengifo & DeWitt, 2019; Turney & Halpern-Meekin, 2021; Turney & Schneider, 2016), stigma (Feingold, 2021), and loss of social status (Schnittker & Bacak, 2013). Emerging research proposes that the stress-related harms of incarceration can contribute to a weathering process that inhibits healthy aging and exacerbates cognitive decline (Testa et al., 2023).

Age-related cognitive decline is a well-documented phenomenon with significant implications for public health (Centers for Disease Control and Prevention, 2019; Sinclair & LaPlante, 2019). As individuals advance in age, they commonly experience a gradual decline in some aspects of cognitive function and memory recall. This decline can manifest in various forms, such as reduced processing speed, decreased working memory capacity, and impaired episodic memory (Deary et al., 2009; Murman, 2015). These cognitive changes can profoundly affect older adults’ daily functioning and quality of life (Altieri et al., 2021). Understanding the nature and trajectory of cognitive decline with age—and how incarceration as a life stressor might serve as a risk factor for cognitive decline—is essential for developing public health strategies to promote cognitive health and healthy aging.

A small but growing literature generally finds elevated levels of cognitive impairment among those with prior incarceration experiences. Indeed, studies show more mild cognitive impairment and dementia using Medicaid records among primarily male formerly incarcerated veterans (Kuffel et al., 2021, 2022). A series of other studies also found associations between prior incarceration and cognitive impairment status from the Telephone Interview for Cognitive Status measure among middle-aged formerly incarcerated adults from the National Longitudinal Survey of Youth—1997 (Cox & Wallace, 2022) and older adults over 55 years old from the Health and Retirement Study (Tanksley et al., 2023; Testa et al., 2023).

The relatively few studies on this topic remain limited in ways that are addressed in the current study. Namely, existing research data comprises predominantly male samples (Kuffel et al., 2021, 2022; Tanksley et al., 2023; Testa et al., 2023). Although this is partly expected due to the higher incarceration rates among men in the United States (Carson & Kluckow, 2023), there is less understanding of how incarceration affects the cognition of women later in life, despite research suggesting that women may experience more accelerated cognitive decline as they age as compared to men (Jack et al., 2015; Levine et al., 2021; Mielke et al., 2014) and female incarceration rates have increased faster than male incarceration rates over the past five decades (Heimer et al., 2023). Importantly, one recent study found that women who were previously incarcerated had a greater risk for cognitive impairment compared to previously incarcerated men with a similar background (Tanksley et al., 2023).

Using recent data from a national sample of older adults in the United States, the current study aims to investigate the relationship between prior incarceration and an aspect of executive cognitive functioning as measured by interviewer-administered word recall tests.

Data

Data are from the National Longitudinal Study of Adolescent to Adult Health—Parent Study (AHPS). The AHPS gathered social, behavioral, and health survey data in 2015–2017 on a probability sample of the parents of children selected to participate in the prospective cohort study of the National Longitudinal Study of Adolescent to Adult Health (Add Health), who were originally interviewed in 1994–1995. Data were collected from 2,013 parents, ranging in age from 47 to 82 (mean age 62) years old. Parents eligible for participation in this study were the biological parents, adoptive parents, or stepparents of an Add Health respondent in 1994–1995; not deceased or incarcerated at the time of AHPS sampling; and had at least one Add Health child who was also not deceased at the time of AHPS sampling (Eischen et al., 2019). Because most parent respondents were mothers, the sample is more than 96% female.

Dependent Variables

The AHPS administered word recall memory exercises to the parent respondent from the Rey Auditory-Verbal Learning Test (RAVLT). Field interviewers were directed to move the computer so the respondent could not see the screen display. The instrument displayed 15 words to the interviewer to be read to the respondent. After the Field Interviewers read the 15 words, they asked respondents to repeat them; a timer on the screen controlled the countdown. Field Interviewers marked all the words the respondent remembered on a Word Recall Form in 90 s to measure immediate or short-term verbal memory. Following the 90-s Word Recall, the respondent was asked again to report as many of the initial 15 words as they could remember to conclude the Word Recall exercise. Respondents had 60 s to measure delayed or long-term verbal memory the second time.

Accordingly, the dependent variable for this analysis includes the number of words recalled on the (a) 90-s (immediate or short-term verbal memory), (b) 60-s recall tests (delayed or long-term verbal memory), and (c) combined word recall on the 90-s and 60-s tests (Bean, 2011; Hawkins et al., 2021).

Independent Variable

Prior incarceration is measured from the question, “Have you ever been incarcerated, that is, spent time in a jail, prison, juvenile detention center or other correctional facility?” (yes or no).

Control Variables

Models are adjusted for several demographic, socioeconomic, and health-related variables, including respondent sex (female or male), age in years, race/ethnicity (non-Hispanic White, non-Hispanic Black, Hispanic, or other race), highest educational attainment (high school or less, some college, college graduate, or postgraduate), if a respondent had been previously abused by a parent (yes or no) or a partner (yes or no), whether a respondent is receiving public assistance benefits (yes or no), self-rated health (poor/fair vs good/very good/excellent), body mass index (underweight, healthy weight, overweight, or obese), frequency of alcohol consumption (never, monthly or less, 2–4 times per month, 2–3 times per week, or 4+ times per week), if a respondent ever smoked cigarettes (yes or no), whether a respondent has received a dementia diagnosis (yes or no), family history of dementia among parents, siblings, aunts or uncles, or grandparents (yes or no), and the year of data collection (2015, 2016, or 2017).

Statistical Analysis

The association between prior incarceration and the number of words recalled is assessed using multiple Poisson regression. We first estimate the bivariate association and then include control variables. Because cognition declines with age and the studies focus on older adults, we assess the results stratified by the full sample and those older than 60 years (Deary et al., 2009; Murman, 2015). Missing data on the covariables were addressed using multiple imputation with chained equations using 20 multiply imputed data sets and an analytic sample of 2,003 respondents. Analyses were performed in STATA v. 17.0, and all analyses used survey weights and robust standard errors.

Results

Table 1 provides the summary statistics for the analytic sample. Approximately 4.2% of the sample reported having a prior incarceration. The average total word recall is 9.91 words (range 0–27), with an average of 5.67 words for 90-s recall (range = 0–15) and 4.24 for 60-s word recall (range = 0–14).

Table 1.

Weighted Summary Statistics of Analytic Sample (N = 2,003)

Variables Mean Standard deviation % Minimum Maximum
Dependent variables
 Total word recall 9.78 3.25 0 27
 90-s word recall 5.60 1.77 0 15
 60-s word recall 4.19 1.78 0 14
Independent variable
 Prior incarceration 4.8 0 1
Age 62.27 5.68 47 82
Race/ethnicity
 White 69.6 0 1
 Black 12.7 0 1
 Hispanic 10.3 0 1
 Other race 7.3 0 1
Educational attainment
 Less than high school 10.6 0 1
 High school graduate 30.9 0 1
 Some college 32.7 0 1
 College graduate 15.0 0 1
 Postcollege 10.7 0 1
History of abuse
 Abused by parent 14.1 0 1
 Abused by partner 16.3 0 1
Public assistance recipient 4.3 0 1
Poor/fair self-rated health 30.0 0 1
Body mass index
 Underweight 1.2 0 1
 Healthy weight 24.1 0 1
 Overweight 31.7 0 1
 Obese 43.0 0 1
Alcohol consumption
 Never 44.5 0 1
 Monthly or less 27.6 0 1
 2–4 times per month 12.5 0 1
 2–3 times per week 8.8 0 1
 4 or more times per week 6.6 0 1
Ever smoked 45.8 0 1
Family history of dementia 28.8 0 1
Personal dementia diagnosis 1.3 0 1
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Table 2 Panel A displays the Poisson regression of the total word for the combined 90-s and 60-s tests on prior incarceration. The findings show that among the full sample, incarceration history is associated with 11% lower word recall in the bivariate analysis (incidence risk ratio [IRR] = 0.889, 95% confidence interval [CI] = 0.815, 0.971) and an 8.5% lower word recall after including control variables (IRR = 0.915, 95% CI = 0.840, 0.997). Restricting the sample to respondents over 60 and including control variables, incarceration is associated with a 15% reduction in total word recall (IRR = 0.847, 95% CI = 0.752, 0.954).

Table 2.

Multiple Poisson Regression of Word Recall on Prior Incarceration and Covariables

Panel Bivariate analysis
(N = 2,003)		 With control variables
(N = 2,003)		 With control variables and over age 60 (n = 1,208)
IRR 95% CI IRR 95% CI IRR 95% CI
A: Total word recall 0.889** (0.815–0.971) 0.915* (0.840–0.997) 0.847** (0.752–0.954)
B: 90-s word recall 0.872** (0.787–0.966) 0.902* (0.817–0.996) 0.857** (0.762–0.963)
C: 60-s word recall 0.912† (0.832–1.000) 0.933 (0.852–1.022) 0.834* (0.713–0.974)
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Notes: IRR = incidence rate ratio.

Control variables include respondent sex, respondent age, respondent race/ethnicity, highest educational attainment, abused by a parent, abused by a partner, public assistance recipient, self-rated health, body mass index, alcohol use, ever smoked, dementia diagnosis, family history of dementia, and survey year.

*** p < .001.

** p < .01.

* p < .05.

† p < .10.

Table 2, Panel B provides the results for the 90-s recall. The bivariate results demonstrate an approximately 13% lower word recall among formerly incarcerated persons (IRR = 0.872, 95% CI = 0.787, 0.966), which is reduced to about 10% after including control variables (IRR = 0.902, 95% CI = 0.817, 0.996). When restricting the sample to respondents over 60 and including control variables, incarceration is associated with a 15% lower rate of word recall (IRR = 0.857, 95% CI = 0.752, 0.963).

Table 2, Panel C focuses on the 60-s recall. The bivariate association shows that incarceration is associated with a 9% reduction in 60-s word recall, and the relationship is marginally statistically significant with a p value of .051 (IRR = 0.912, 95% CI = 0.832; 1.000). After including control variables, the results are not statistically significant. Finally, when restricting the sample to those over age 60 and including control variables, we find that incarceration is associated with a 17% reduction in number of words recalled using the 60-s word recall (IRR = 0.834, 95% CI = 0.713, 0.974).

Finally, Supplementary Table 1 provides a supplemental analysis only on the female subsample. The results show that the magnitude of the coefficients across models remains substantively similar to the main results reported in Table 2.

Discussion

The findings from this study provide new evidence that formerly incarcerated older adults experience poorer cognition, at least in terms of short-term and long-term verbal recall, than their never-incarcerated counterparts, especially among respondents over age 60. These results from a new data source are consistent with prior research indicating that the lasting impact of incarceration extends well into the later stages of life (Garcia-Grossman et al., 2023; Williams et al., 2012), with specific harms to cognitive functioning (Cox & Wallace, 2022; Kuffel et al., 2021; Kuffel et al., 2022; Tanksley et al., 2023; Testa et al., 2023).

Our results emphasize the need to develop and test targeted interventions to promote cognitive health among formerly incarcerated older adults. There has been growing literature on the effectiveness of cognitive remediation interventions that have shown some success, particularly in some clinical populations (Radhakrishnan et al., 2016; Vita et al., 2021), but more rigorous research is needed to evaluate their effects on aging adults and those with histories of incarceration, especially among formerly incarcerated older women who make up growing numbers of the incarcerated population (Heimer et al., 2023) and may be especially prone to cognitive decline and health consequences due to incarceration (Latham-Mintus et al., 2022; Tanksley et al., 2023). Early identification of cognitive impairment within this population through the early integration of cognitive screening into routine health assessments immediately upon incarceration and as part of the reentry process can facilitate timely interventions, potentially mitigating the progression of cognitive decline and enhancing the quality of life (Baillargeon et al., 2023). Additionally, our study underscores the importance of policy reforms within the criminal justice system, such as improving access to health services during incarceration, facilitating a smoother transition to healthcare and social services upon reentry, and ensuring that such services are particularly available for older persons. One such approach is greater investment in transition clinics—community health clinics that serve formerly incarcerated individuals—focusing on geriatric care to better support cognitive health needs among older, formerly incarcerated individuals (Fox et al., 2014; Shavit et al., 2017). Overall, these approaches may help to detect cognitive impairment, support the cognitive health of older adults with incarceration experiences, and reduce the broader societal burden associated with cognitive decline in this population, ultimately advancing health equity.

Limitations and Future Directions

Although the findings of this study offer contributions to the literature, some limitations should be noted. First, the measure of incarceration is a binary item that does not discern potentially important features, including the duration of incarceration, the number of times incarcerated, when an individual was incarcerated, and experiences endured during incarceration. Second, the sample size did not permit us to analyze how the findings would differ by racial and ethnic background. Third, the study only assessed cognitive function using word recall at one-time point, and a full neurocognitive battery was not administered. Thus, our findings are only related to one aspect of executive functioning. Future research that uses larger samples and validated measures of cognitive functioning would be valuable in advancing the work we have started here. In particular, it is essential to delve deeper into the mechanisms through which incarceration experiences affect cognitive health. Finally, given the AHPS sampling frame, this sample is not generalizable to all Americans within the observed age range.

Conclusion

The findings of this study shed light on the cognitive challenges formerly incarcerated older adults face and contribute to understanding the long-lasting implications of incarceration for cognitive function as individuals age. Building additional knowledge in this area is essential for developing targeted interventions, and policy reforms that promote cognitive well-being are paramount to ensure that interventions are equitable and effective in reducing cognitive disparities across the lifespan.

Supplementary Material

gbae040_suppl_Supplementary_Table_S1
gbae040_suppl_supplementary_table_s1.docx (16.6KB, docx)

Contributor Information

Alexander Testa, Department of Management, Policy, and Community Health, University of Texas Health Science Center at Houston, Houston, Texas, USA.

Dylan B Jackson, Department of Population, Family, and Reproductive Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.

Meghan Novisky, Department of Criminology and Sociology, Cleveland State University, Cleveland, Ohio, USA.

Kyle T Ganson, Factor-Inwentash Faculty of Social Work, University of Toronto, Toronto, Ontario, Canada.

Jason M Nagata, Department of Pediatrics, University of California, San Francisco, San Francisco, California, USA.

Jack Tsai, Department of Management, Policy, and Community Health, University of Texas Health Science Center at Houston, Houston, Texas, USA; National Center on Homelessness Among Veterans, United States Department of Veterans Affairs, Washington, District of Columbia, USA.

Funding

This research uses data from Add Health Parent Study (2015–2017), funded by the National Institute on Aging of the National Institutes of Health under the following awards: The Add Health Parent Study: Phase I (award RO1AG042794) and Locating the Parents of Add Health (award 21 AG042663-01). The views presented are of the authors alone and do not represent the views of the U.S. Department of Veterans Affairs or any other federal agency.

Conflict of Interest

None.

Data Availability

The data supporting this study’s findings are available from the National Longitudinal Study of Adolescent to Adult Health. Restrictions apply to the availability of these data, which were used under license for this study. Data can be requested from https://addhealth.cpc.unc.edu/data/

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

gbae040_suppl_Supplementary_Table_S1
gbae040_suppl_supplementary_table_s1.docx (16.6KB, docx)

Data Availability Statement

The data supporting this study’s findings are available from the National Longitudinal Study of Adolescent to Adult Health. Restrictions apply to the availability of these data, which were used under license for this study. Data can be requested from https://addhealth.cpc.unc.edu/data/

Articles from The Journals of Gerontology Series B: Psychological Sciences and Social Sciences are provided here courtesy of Oxford University Press

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