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Article

A Cross-Sectional and Longitudinal Analysis of Cognitive Function and Well-Being of Older Adults in Panama During the COVID-19 Pandemic

by
Stephanie Lammie
1,2,
Sofía Rodríguez-Araña
1,3,
Camilo Posada Rodríguez
1,4,
Julio Flores-Cuadra
1,5,6,7,
Ambar Pérez-Lao
1,8,
Gabrielle B. Britton
1,9,10,11,*,
Diana C. Oviedo
1,3,11,* and
Adam E. Tratner
9,11,*
1
Neuroscience Group, Instituto de Investigaciones Científicas y Servicios de Alta Tecnología (INDICASAT-AIP), Panama City 0843-01103, Panama
2
Escuela de Psicología , Universidad Latina de Panamá, Panama City 0823-00933, Panama
3
Escuela de Psicología, Universidad Santa María La Antigua, Panama City 0819-08550, Panama
4
Department of Psychology, The Pennsylvania State University, Center Valley, PA 18034, USA
5
Department of Biology, The Pennsylvania State University, University Park, PA 16802, USA
6
Neuroscience Graduate Program, The Huck Institutes of the Life Sciences, University Park, PA 16802, USA
7
Penn State Neuroscience Institute, The Pennsylvania State University, University Park, PA 16802, USA
8
Department of Clinical and Health Psychology, University of Florida, Gainesville, FL 32603, USA
9
Florida State University, Panama City 0819-05390, Panama
10
Cevaxin, Panama City 0830-00507, Panama
11
Sistema Nacional de Investigación (SNI), La Secretaría Nacional de Ciencia, Tecnología e Innovación (SENACYT), Panama City 0816-02852, Panama
 
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*
Authors to whom correspondence should be addressed.
COVID 2025, 5(8), 128; https://doi.org/10.3390/covid5080128
Submission received: 30 June 2025 / Revised: 4 August 2025 / Accepted: 5 August 2025 / Published: 7 August 2025
(This article belongs to the Special Issue COVID and Public Health)
Browse Figure
Versions Notes

Abstract

The COVID-19 pandemic exacerbated mental illness, accelerated cognitive decline, and deepened social inequalities. In low and middle-income countries (LMIC) such as Panama, it is unclear as to whether, and to what extent, the pandemic lockdowns affected cognitive, mental, and physical health of older adults. This study investigated changes in cognitive function, mental health, and physical health in a sample of Panamanian older adults assessed before and during the pandemic, and examined whether sociodemographic variables were associated with cognition and mental health. Participants completed in-person interviews between 2018 and early 2020 and a follow-up telephone interview between February and May 2021. Repeated measures analyses showed no significant changes in cognitive function or depression; however, participants reported fewer chronic illnesses. Linear regression analysis indicated that higher cognitive function during the pandemic was associated with younger age, higher education, and having sufficient income. An attrition analysis compared participants who completed both interviews to those who were lost to follow-up, revealing that participants who dropped out of the study had lower socioeconomic status and greater impairment at baseline. These findings highlight the need for targeted support for vulnerable older adults during public health crises.

1. Introduction

The COVID-19 pandemic (SARS-CoV-2, 2019) was an unprecedented public health crisis that challenged health systems across the globe [1]. In response to the virus’s rapid spread, governments implemented stringent biosecurity measures (i.e., lockdowns) to reduce disease transmission. The lockdowns precipitated economic recessions, unemployment, and financial instability, which deepened social inequalities worldwide [2]. A growing body of evidence also suggests that the pandemic lockdowns prompted widespread mental illness, learning loss, and accelerated cognitive decline [3,4]. These effects were especially pronounced among vulnerable groups, such as older adults and individuals with low income, limited social support, chronic health conditions, or psychiatric diagnoses, and those grieving the loss of loved ones [1,5,6,7].
Like many other low- and middle-income countries (LMICs) in Latin America, Panama experienced a sudden economic downturn and severe strain on its healthcare system during the height of the pandemic, which further amplified existing socioeconomic and health disparities [8,9,10,11]. The country also enacted some of the strictest lockdown measures globally [12,13,14,15]. Starting in March 2020, all non-essential in-person activities, including compulsory education and religious ceremonies, were suspended. Residents were only permitted to leave their homes on specific days and times, based on their sex and identification number. Additional restrictions—including curfews, dry laws, and travel bans during weekends and holidays—were implemented to further curb social interaction. Public perception reflected widespread concern over the long-term economic and psychological toll of the pandemic on Panamanian society [16,17]. A 2021 survey conducted during the lockdowns reported high rates of mental health disorders and unemployment. Most participants indicated that the pandemic had negatively affected their mental health, income, and social relationships [18].
Research from previous outbreaks has consistently linked lockdown measures with the onset or worsening of mental health conditions [19,20,21,22]. Symptoms such as low mood, irritability, insomnia, post-traumatic stress, anger, emotional exhaustion, loneliness, and elevated levels of depression and anxiety have been associated with social isolation and the stress and uncertainty brought about by the pandemic [23,24,25]. Meta-analyses [25] have shown that the largest and most consistent effect was found for depression symptoms (SMC = 0.216). In addition to psychiatric symptoms, COVID-19 has been linked to cognitive impairments, including difficulties in working memory, divided attention, information processing, mental fatigue, brain fog, and memory loss [4,26,27]. Long-term follow-up studies have documented reduced cognitive performance, with key predictors including comorbidities, being female, and lower education [4,28,29]. For instance, one study showed that the strongest predictors of cognitive performance were being female (HR = 2.57), older (HR = 1.98), and having lower education attainment. Specifically, a one-year decrease in education was linked to reduced cognitive performance (HR = 0.84) and higher comorbidity burden (HR = 1.34) [28]. Risk factors such as isolation, lack of perceived social support, and living alone have also been associated with increased anxiety, depression, and poorer cognitive functioning [30,31].
Studies investigating social determinants of health during the pandemic indicate that mental health outcomes—such as anxiety, depression, and panic attacks—were related to sociodemographic variables including sex, age, education, marital status, socioeconomic level, employment, and lifestyle [32,33]. Cognitive function during the pandemic was similarly associated with factors such as being female, older age, lower education, and socioeconomic disadvantage [34]. It follows that age plays a critical role in how these sociodemographic factors relate to psychosocial outcomes, particularly during public health crises like the COVID-19 pandemic [35].
It has been argued that one of the most affected groups was adults aged 60 and over, due to their higher mortality risk [36]. Aging is associated with weakened immune response, chronic health conditions, and a heightened risk of serious complications from infection [37]. Older adults during the pandemic frequently reported moderate stress levels, psychosomatic symptoms, sleep disturbances, and depression, as well as reduced ability to perform daily activities and decreased autonomy due to enforced isolation [38,39,40]. Several recent studies have further highlighted that social isolation, loneliness, and reduced physical and cognitive stimulation during lockdowns were significantly associated with cognitive decline, depressive symptoms, and anxiety in older adults [23,26,27]. Meta-analyses and longitudinal studies across various countries found increased rates of subjective cognitive complaints, worsening of pre-existing dementia symptoms, and the emergence of new cognitive impairments in previously healthy individuals [28,29]. Notably, depression frequently emerged as a key mediator between isolation and cognitive decline, especially among women and those with lower education levels. Interestingly, despite their physical vulnerability, older adults generally demonstrated better psychological resilience compared to younger adults, who reported higher levels of stress, anxiety, and depression [18,41,42].
It remains an open question as to whether, and to what extent, the pandemic lockdowns in Panama affected the health and psychological functioning of older adults. This study aimed to examine changes in cognitive function, physical health, and depression in a sample of Panamanian older adults assessed before and during the pandemic. We hypothesized that participants would demonstrate lower cognitive function (H1), have more chronic illnesses (H2), and report more depression symptoms (H3) during the pandemic compared to before the pandemic.

2. Materials and Methods

This was a longitudinal and cross-sectional examination of older adults in Panama during the COVID-19 pandemic. The research study was approved by the Social Security Institutional Bioethics Committee of the Social Security Fund (CIEI-CSS-M-064-2022). All participants provided written informed consent. Participation was voluntary and confidential; no personal identifying information, such as name or address, was included in the database.

2.1. Participants and Procedure

This research included a sample of older adult participants enrolled in the Panama Aging Research Initiative- Health Disparities (PARI-HD) study [43,44], an ongoing community-based longitudinal study investigating cognitive aging in Panama. The research team advertised the study on social media platforms and divulged the study in public outreach events to recruit a convenience sample of participants. Individuals were eligible to participate in the study if they were an older adult (≥60 years of age) living in Panama, and were excluded from participation if they were hospitalized or institutionalized due to a physical or mental health condition at the time of enrollment, or had a condition that precluded them from answering written questions (e.g., visual impairment, intellectual disability, illiteracy). Prospective participants who met these criteria were recruited and provided informed consent in compliance with the Declaration of Helsinki.
All participants underwent an in-person clinical interview between April 2018 and March 2020. A total of 466 dementia-free residents of Panama (76.2% women), with an average age of 70.6 years (SD = 6.7, Range = 60–93.9) were interviewed during that time prior to the COVID-19 pandemic. Participants were relatively educated (Mean years of education = 15.9, SD = 4.6) and affluent, with 76.3% of participants earning a monthly income (≥850$) above the median income of Panama. In-person interviews were suspended in March 2020 due to the COVID-19 pandemic. Afterward, all participants were contacted via telephone, of which 228 participants (78.9% women; Mage = 70.1 years, SDage = 5.8, Rangeage = 60–90.6) (Figure 1) were interviewed between February 2021 and May 2021. The average time elapsed between the pre-pandemic clinical interview and mid-pandemic telephone interview was 17 months. Both interviews were conducted in Spanish and administered by trained research personnel.

2.2. Measures

During the pre-pandemic clinical interview, participants provided the following sociodemographic information: sex, age, current or former occupation, monthly income (in United States Dollars $), and years of education. Participants also self-reported how many chronic illnesses (e.g., diabetes, hypertension) that they had been diagnosed with. Basic activities of daily living (BADL) were assessed using the Katz Index [45] (bathing, dressing, toileting, transferring, continence and feeding), and instrumental activities of daily living (IADL) were assessed using the Lawton & Brody Index [46] (telephoning, shopping, food preparation, housekeeping, laundering, use of transportation, and managing finances and medications). IADL scores were adjusted in cases where individuals had never performed a particular activity. Cognitive function was measured using the 30-item Spanish version of the Mini-Mental State Examination (MMSE) [47]. Depression symptoms were measured using the Geriatric Depression Scale (GDS-15) [48].
Due to the constraints of interviewing participants remotely, the mid-pandemic telephone interview was shortened and used scale measures designed for telephone interviews. It included the same sociodemographic questions as the pre-pandemic clinical interview, with an additional question assessing whether participants’ income was sufficient to cover all their living expenses during the lockdown. Participants similarly self-reported the number of chronic illnesses they had been diagnosed with until the time of the telephone interview. The Patient Health Questionnaire-9 (PHQ 9) [49] was used to measure the frequency of depression symptoms (i.e., not at all, several days, more than half of the days, nearly every day). The Generalized Anxiety Disorder—7 (GAD 7) [50] was included to assess the frequency of generalized anxiety symptoms (i.e., not at all, several days, more than half of the days, nearly every day). Finally, an abbreviated version of the Montreal Cognitive Assessment designed for telephone interviews (T-MoCA) [51], was used to measure cognitive function.

2.3. Statistical Analyses

Statistical analyses were conducted using IBM SPSS Statistics version 29.0. Repeated measures analyses were used to investigate physical and psychological changes from the pre-pandemic clinical interview to the mid-pandemic telephone interview. MoCA scores were converted to MMSE scores [52], and scores for GDS-15 and PHQ9 were converted to standardized z-scores for repeated measures analyses. Simultaneous multiple linear regressions explored associations between variables during the pandemic. A multivariate analysis compared, at baseline, the participants who completed pre- and mid-pandemic interviews to participants who only attended the pre-pandemic interview. Missing data were removed from analyses via listwise deletion. Results for which p < 0.05 were accepted as statistically significant.

3. Results

3.1. Repeated Measures Analyses of Variance

Three separate repeated measures analyses of variance (ANOVA) assessed changes in cognitive function, chronic health conditions, and depression symptoms from the pre-pandemic interview to mid-pandemic interview. Results indicated that the number of self-reported chronic illnesses decreased significantly between interviews [F(1, 226) = 4.52, MSE = 45.04, ηp2 = 0.02, p = 0.035]. Participants reported an average of 1.9 chronic illnesses before the pandemic, compared to 1.2 chronic illnesses during the pandemic. However, there were no significant differences in cognitive function [F(1, 226) = 2.33, MSE = 13.34, ηp2 = 0.01, p = 0.129] or depression [F(1, 226) = 2.42, MSE = 1.55, ηp2 = 0.01, p = 0.121] when comparing participants’ scores across the two interviews. Table 1 summarizes the results of these three longitudinal analyses.

3.2. Multiple Linear Regression Analyses

Next, three multiple linear regression analyses examined whether sociodemographic variables were associated with cognitive function, depression, and anxiety during the pandemic. Cognitive function, depression, and anxiety were separately regressed on to sex, age, years of education, number of chronic illnesses, and whether their income was sufficient to cover living expenses. The overall model was significant for cognitive function [F(5, 222) = 9.01, MSE = 2.78, R2 = 0.17, p < 0.001] and indicated that younger age (β = −0.23, t = −3.48, p < 0.001), being more educated (β = 0.22, t = 3.42, p < 0.001), and having sufficient income (β = 0.18, t = 2.92, p = 0.004) was associated with higher cognitive function during the pandemic. Sex and number of chronic illnesses were not significantly related to cognition (Table 2). The models predicting depression [F(4, 223) = 1.26, MSE = 1.86, R2 = 0.02, p = 0.287] and anxiety [F(4, 223) = 2.10, MSE = 2.04, R2 = 0.04, p = 0.080] did not fit, suggesting that the sociodemographic variables were not significantly related to mental health symptoms.

3.3. Attrition Analysis

Of the 466 participants who participated in the clinical interview prior to the pandemic, 228 (48.9%) completed the telephone interview during the mid-pandemic lockdown, whereas 238 participants could not be reached or declined to participate at follow-up. We performed an attrition analysis to compare the subsample of participants who did not complete the mid-pandemic telephone interview to the subsample of participants who attended both the pre- and mid-pandemic interviews. A multivariate analysis of variance (MANOVA) compared the pre- and mid-pandemic interviews to inspect whether there were differences in age, years of education, cognitive function, monthly income, number of chronic health conditions, depression symptoms, and basic and instrumental activities of daily living. The omnibus test was significant [Wilks’ Lambda = 0.93, F(8, 453) = 4.52, p < 0.001, ηp2 = 0.07]. Between-subjects tests indicated significant differences in cognitive function [F(1) = 6.58, p = 0.011, ηp2 = 0.01], depression symptoms [F(1) = 5.21, p = 0.023, ηp2 = 0.01], years of education [F(1) = 18.53, p < 0.001, ηp2 = 0.04], monthly income [F(1) = 16.38, p < 0.001, ηp2 = 0.03], and instrumental activities of daily living [F(1) = 7.23, p = 0.007, ηp2 = 0.02], but not age, number of chronic health conditions, or BADL (ps > 0.05). The overall results revealed that participants who did not attend the follow-up telephone interview during the pandemic had significantly lower cognitive function, more depression symptoms, less years of education, lower monthly income, and could not perform as many IADL compared to participants who attended both interviews. However, there were no significant differences in age, number of chronic health conditions, or performance of BADL between groups (Table 3).

4. Discussion

The primary goal of this study was to investigate if there were changes in cognitive function, physical health, and mental health in a sample of Panamanian older adults assessed before and during the pandemic. The overall results did not support the study’s hypotheses (H1–H3). Exploratory analyses examined whether key sociodemographic factors—sex, age, education, chronic health conditions, and having sufficient income—were associated with cognitive function and mental health, finding that only cognitive function was related to sociodemographic variables.
Participants did not show any significant changes in depression over time. These findings deviate from many studies in which people reported more symptoms of mental illness during the pandemic [38,53,54,55]. Though, some research suggests that individuals were more distressed and depressed early in the pandemic, and symptoms gradually subsided as individuals adapted to the situation over time [56]. The timing of the mid-pandemic interview (spring 2021) potentially explains why there was no observed difference in depression between the two interviews, because any increase in depression symptoms might have occurred earlier in the pandemic (e.g., spring 2020) and then decreased back to baseline levels by the time of the mid-pandemic interview. Participants may have developed coping strategies or simply adapted to the pandemic lockdowns by 2021 [57]. Additionally, studies on the psychosocial effects of the pandemic in Panama showed that older adults reported lower depression, anxiety, and stress, were more resilient, and overall felt less affected by the pandemic compared to younger adults [18,41], which may also account for why this sample of older adults reported no change in depression symptoms.
Likewise, there were no significant differences in cognitive function between the two interviews, contrary to other research that showed decreased cognitive function in older adults during the pandemic [4,29,58]. This result may be due, in part, to the characteristics of the sample. Most participants were college-educated and reported earning a higher monthly income than the median income of Panamanian adults. Individuals with more years of formal education often benefit from greater cognitive reserve, which may protect against the impact of age and stressors like the pandemic [59,60,61]. Financial security also plays a critical role in cognitive health by reducing chronic stress and increasing access to stimulating environments and resources [62,63]. Hence, participants may not have experienced changes in cognitive function over time owing to the protective effects of higher education and income on cognition.
Participants unexpectedly reported fewer chronic illnesses during the pandemic than before the pandemic, in contrast with research documenting physical deterioration during the COVID-19 pandemic [53,64]. This was surprising given that COVID-19 itself frequently caused health complications and exacerbated preexisting illnesses, particularly in older populations [65]. This may suggest that participants improved their physical health over time; however, we interpret this finding with caution. During the pandemic, many individuals avoided visiting medical centers due to fears of COVID-19 exposure or had difficulty getting appointments due to healthcare system strain [66,67]. It is possible that participants received health assessments less frequently during the pandemic and may not have considered chronic health conditions that were not under treatment. As a result, participants could have underreported chronic illnesses at the time of the mid-pandemic interview.
Moreover, regression analyses revealed that being younger, more educated, and having sufficient income to cover living expenses was associated with higher cognitive function during the pandemic. This is in line with a large body of research on protective factors for cognitive aging [7,32,33,68,69]. Although participant income (USD) was not assessed during the mid-pandemic interview, participants who reported that they had sufficient income to cover their expenses may have benefited cognitively via a reduction in stress and/or greater access to stimulating experiences during the pandemic. However, the regression models predicting depression and anxiety were not statistically significant. This contrasts with numerous studies linking sociodemographic factors, such as lower socioeconomic status and poorer physical health, to symptoms of mental illness during the pandemic [33,70]. Other factors—such as social isolation and preexisting mental illness—may explain variation in depression and anxiety during the COVID-19 lockdowns above and beyond sociodemographic characteristics [30,71], whereas cognition may be more influenced by sociodemographic characteristics such as age, education, and income.
The overall pattern of findings highlights the possibility that older adults in Panama were not as adversely impacted by the pandemic as other adult cohorts. Alternatively, the sample may not have included individuals who were most vulnerable to pandemic-related distress and hardship. To address this, we investigated whether participants with lower socioeconomic status and who were more impaired disproportionately dropped out of the study. More than half of the participants (51%) who were interviewed before the pandemic did not participate in the follow-up interview. This aligns with other longitudinal studies conducted during the COVID-19 pandemic, which often faced similar challenges in maintaining participant engagement [56,70]. Our analyses showed that those who did not complete the second interview were on average, less educated, received less monthly income, had lower cognitive function, had more depressive symptoms, and performed fewer IADL compared to the subgroup of participants who remained in the study when compared at baseline. These findings are consistent with prior research showing that individuals with lower cognitive function and worse mental health are less likely to participate in follow-up assessments [72,73]. The reduced independence in IADL observed in non-responders may also suggest greater functional impairment, which could have made participation in a telephone-based interview more challenging during the lockdown period [74]. Hence, the most vulnerable older adults—those struggling with daily activities, financial insecurity, or cognitive and emotional challenges—may have experienced greater declines during the pandemic but were underrepresented due to attrition.

5. Limitations and Strengths

This study had several limitations. The use of a convenience sample reduces the study’s generalizability, because the sample is not representative of the population. Specifically, the study disproportionately recruited educated, female, middle-class, and urban community members. Because this cohort of older adults was, on average, wealthier than the general population of Panama, they may have had access to high quality healthcare services, medication, supermarkets, entertainment, and other lifestyle determinants of health (e.g., diet, exercise) that mitigated chronic illness, psychological distress, and cognitive decline during the pandemic [43,44]. Vulnerable groups, such as economic migrants and people from impoverished communities in rural areas outside the capital city, were not included in the sample. Therefore, the results may not generalize to other older adults in the population.
The attrition analysis revealed notable differences between participants who remained in the study and those who were lost to follow-up. The two subgroups of participants did not initially differ in age or number of chronic illnesses, suggesting that attrition might have not been due to physical health or age, but to other psychosocial and functional variables, or related to socioeconomic status, cognitive reserve, and emotional well-being [75]. For instance, lower income may have limited participants’ ability to contact friends and family or access remote health services during the pandemic [76]. This calls into question the reliability of the results of the repeated measures and regression analyses, as the results likely reflect outcomes for those with better access to resources, higher education, and stronger functional capacity. Another limitation was the study design, which precludes determining the causes for the reduction in chronic illness over time, as well as the causal linkages between sociodemographic variables and cognitive function.
Despite these limitations, the current study included a relatively large sample of participants, which conferred higher statistical power to the within and between-subjects analyses, thereby strengthening its validity. This is among the few studies to examine cognitive function and well-being of older adults in the Latin American context and increases the representation of LMIC populations in research on older adults during the COVID-19 pandemic.

6. Conclusions

This is the first cross-sectional and longitudinal study examining older adults prior to and during the COVID-19 pandemic in Panama. These findings contribute to a growing body of work on aging during the COVID-19 pandemic, which may inform public policies that safeguard vulnerable populations during public health crises. They highlight the need to address social and technological barriers to participation in longitudinal research, especially during times of crisis such as the COVID-19 pandemic. Future studies should ensure that at-risk populations are not overlooked.

Author Contributions

Conceptualization, G.B.B. and D.C.O.; methodology, A.P.-L., D.C.O., A.E.T. and G.B.B.; formal analysis, A.E.T.; investigation, D.C.O. and G.B.B.; resources, A.E.T., D.C.O. and G.B.B.; writing—original draft preparation, S.L., S.R.-A. and A.E.T.; writing—review and editing, A.E.T., D.C.O., G.B.B., S.R.-A., S.L., C.P.R., A.P.-L. and J.F.-C.; supervision, D.C.O., G.B.B. and A.E.T.; funding acquisition, D.C.O., A.E.T. and G.B.B. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by Sistema Nacional de Investigación (SNI) of Panama, grant numbers [SNI-063-2023; SNI-044-2023; SNI-040-2023]. APL is funded by a doctoral scholarship (IFARHU-SENACYT) from the Secretaria Nacional de Ciencia, Tecnología e Innovación of Panama.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki and approved by the Social Security Institutional Bioethics Committee of the Social Security Fund (CIEI-CSS-M-064-2022).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study. Written informed consent has been obtained from the participants to publish this paper.

Data Availability Statement

The data supporting the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.

Acknowledgments

We thank PARI-HD study participants for their contribution to research, and past and present PARI-HD staff who assisted in data collection and other activities related to the project.

Conflicts of Interest

The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

Abbreviations

The following abbreviations are used in this manuscript:
COVID-19Coronavirus disease 2019
SARS-CoV-2, 2019Severe Acute Respiratory Syndrome Coronavirus 2
PARI- HDPanama Aging Research Initiative- Health Disparities
LMICsLow- and Middle-Income Countries
BADLBasic Activities of Daily Living
IADLInstrumental Activities of Daily Living
MMSEMini-Mental State Examination
GDSGeriatric Depression Scale
PHQ-9Patient Health Questionnaire-9
GAD-7Generalized Anxiety Disorder-7
T-MoCATelephone version of Montreal Cognitive Assessment

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Covid 05 00128 g001
Figure 1. Flowchart of participants in the study.
Figure 1. Flowchart of participants in the study.
Covid 05 00128 g001
Table 1. Repeated measures ANOVAs comparing assessments from the pre-pandemic interview to assessments at the mid-pandemic interview (n = 227).
Table 1. Repeated measures ANOVAs comparing assessments from the pre-pandemic interview to assessments at the mid-pandemic interview (n = 227).
Pre-Pandemic InterviewMid-Pandemic Interviewp-Value
M (SD)M (SD)
Cognitive Function 127.9 (1.7)27.5 (3.4)p = 0.129
Chronic Illnesses (Sum)1.9 (4.5)1.2 (1.0)p = 0.035
Depression Symptoms (Sum)−0.1 (0.9)0.90 (1.0)p = 0.121
Note: M = mean; SD = standard deviation. 1 Cognitive function was measured using the Mini-Mental State Examination (MMSE).
Table 2. Multiple linear regression analysis of sociodemographic factors associated with cognitive function 1 during the pandemic (n = 228).
Table 2. Multiple linear regression analysis of sociodemographic factors associated with cognitive function 1 during the pandemic (n = 228).
VariablebStandard Errorβt
Sex0.690.470.091.50
Age−0.12 ***0.03−0.23−3.48
Education0.15 ***0.050.223.42
Sufficient Income1.34 **0.460.182.92
Chronic Illnesses (sum)−0.120.19−0.04−0.65
Note: 1 Cognitive function was measured using the telephone version of the Montreal Cognitive Assessment (MOCA); Having sufficient income was coded as 0 = No, 1 = Yes. p < 0.01 **, p < 0.001 ***.
Table 3. MANOVA comparing study participants who only completed the pre-pandemic interview to participants who completed both the pre-pandemic and mid-pandemic interviews.
Table 3. MANOVA comparing study participants who only completed the pre-pandemic interview to participants who completed both the pre-pandemic and mid-pandemic interviews.
Total
(n = 462)		Pre-Pandemic Only
(n = 236)		Pre-Pandemic and Mid-Pandemic
(n = 226)		p-Value
M (SD)M (SD)M (SD)
Age (Years)70.6 (6.7)71.1 (7.4)70.1 (5.8)p = 0.112
Education (Years) 15.9 (4.6)15.1 (4.7)16.9 (4.2)p < 0.001
Cognitive Function 127.6 (1.8)27.4 (1.9)27.8 (1.7)p = 0.011
Monthly Income (USD) 2 4.1 (1.8)3.8 (1.9)4.5 (1.7)p < 0.001
Chronic Illnesses (Sum)1.9 (3.4)1.9 (1.5)1.9 (4.6)p = 0.813
Depression Symptoms (Sum)1.8 (2.3)2.0 (2.5)1.5 (2.0)p = 0.023
Lawton & Brody Index7.8 (0.7)7.7 (0.8)7.9 (0.5)p = 0.007
Katz Index5.9 (0.4)5.9 (0.4)5.9 (0.3)p = 0.737
Note: M = mean; SD = standard deviation; 1 cognitive function was measured using Mini-Mental State Examination (MMSE); 2 monthly income was measured using a Likert-scale (0 = ≤250$, 1 = 251–500$, 2 = 501–850$, 3 = 851–1200$, 4 = 1201–1600$, 5 = 1601–2000$, 6 = >2000$); USD = U.S. dollars.
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Lammie, S.; Rodríguez-Araña, S.; Posada Rodríguez, C.; Flores-Cuadra, J.; Pérez-Lao, A.; Britton, G.B.; Oviedo, D.C.; Tratner, A.E. A Cross-Sectional and Longitudinal Analysis of Cognitive Function and Well-Being of Older Adults in Panama During the COVID-19 Pandemic. COVID 2025, 5, 128. https://doi.org/10.3390/covid5080128

AMA Style

Lammie S, Rodríguez-Araña S, Posada Rodríguez C, Flores-Cuadra J, Pérez-Lao A, Britton GB, Oviedo DC, Tratner AE. A Cross-Sectional and Longitudinal Analysis of Cognitive Function and Well-Being of Older Adults in Panama During the COVID-19 Pandemic. COVID. 2025; 5(8):128. https://doi.org/10.3390/covid5080128

Chicago/Turabian Style

Lammie, Stephanie, Sofía Rodríguez-Araña, Camilo Posada Rodríguez, Julio Flores-Cuadra, Ambar Pérez-Lao, Gabrielle B. Britton, Diana C. Oviedo, and Adam E. Tratner. 2025. "A Cross-Sectional and Longitudinal Analysis of Cognitive Function and Well-Being of Older Adults in Panama During the COVID-19 Pandemic" COVID 5, no. 8: 128. https://doi.org/10.3390/covid5080128

APA Style

Lammie, S., Rodríguez-Araña, S., Posada Rodríguez, C., Flores-Cuadra, J., Pérez-Lao, A., Britton, G. B., Oviedo, D. C., & Tratner, A. E. (2025). A Cross-Sectional and Longitudinal Analysis of Cognitive Function and Well-Being of Older Adults in Panama During the COVID-19 Pandemic. COVID, 5(8), 128. https://doi.org/10.3390/covid5080128

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