Chiyoung Lee

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• Lee, C., House, S., Beaudoin, F., Neylan, T., Clifford, G., Linnstaedt, S., Germine, L., Rauch, S., Haran, J., Storrow, A., Lewandowski, C., Musey, P., Hendry, P., Sheikh, S., Punches, B., Swor, R., Hudak, L., Pascual, J., Seamon, M., , Harris, E., et al. (2024). Understanding onset, dynamic transitions, and associated inequality risk factors for adverse posttraumatic neuropsychiatric sequelae after trauma exposure. Psychiatric Research and Clinical Practice. doi:10.1176/appi.prcp.20240017
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  Objective: Several gaps remain in the understanding of the onset, dynamic transitions, and associated risk factors of adverse posttraumatic neuropsychiatric sequelae (APNS) in the acute post-trauma window. Based on serial assessments of symptoms from a large cohort study, we identified homogeneous statuses across multiple APNS symptom domains and investigated the dynamic transitions among these statuses during the first 2 months after trauma exposure. Furthermore, we studied how symptom onset and transitions are affected by equity-relevant characteristics. Methods: The analysis was based on 2557 participants enrolled in the Advancing Understanding of RecOvery afteR traumA (AURORA). APNS symptoms comprised pain, depression, sleep discontinuity, nightmares, avoidance, re-experience, anxiety, hyperarousal, somatic symptoms, and mental fatigue. We identified the homogeneous status of APNS symptoms at baseline, 1 month, and 2 months, and explored transition probabilities among these statuses using latent transition analysis. Equity-relevant characteristics included gender, race, education, family income, childhood trauma, and area deprivation. Results: Three homogeneous statuses–low-, moderate-, and severe-symptom–were identified. While the majority of trauma survivors with severe- or moderate-symptom status maintained the same status over time, some transitioned to a less severe symptom status, particularly within the first month. Specifically, females, non-whites, and those with higher childhood trauma were associated with a decreased likelihood of transitioning to a less severe symptom status. From one to 2 months, lower income was associated with a decreased likelihood of transitioning from moderate-to low-symptom status. Conclusions: The findings can inform early intervention strategies for APNS, potentially reducing health disparities among trauma survivors.
• Lee, C., Park, Y., Cho, B., & Lee, H. (2024). A network-based approach to explore comorbidity patterns among community-dwelling older adults living alone. GeroScience, 46(2). doi:10.1007/s11357-023-00987-z
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  The detailed comorbidity patterns of community-dwelling older adults have not yet been explored. This study employed a network-based approach to investigate the comorbidity patterns of community-dwelling older adults living alone. The sample comprised a cross-sectional cohort of adults 65 or older living alone in a Korean city (n = 1041; mean age = 77.7 years, 77.6% women). A comorbidity network analysis that estimates networks aggregated from measures of significant co-occurrence between pairs of diseases was employed to investigate comorbid associations between 31 chronic conditions. A cluster detection algorithm was employed to identify specific clusters of comorbidities. The association strength was expressed as the observed-to-expected ratio (OER). As a result, fifteen diseases were interconnected within the network (OER > 1, p-value 1.85). Three distinct clusters were identified as follows: (a) cataracts, osteoporosis, chronic otitis media, osteoarthritis/rheumatism, low back pain/sciatica, urinary incontinence, post-accident sequelae, and thyroid diseases; (b) hyperlipidemia, diabetes mellitus, and hypertension; and (c) depression, skin disease, gastric duodenal ulcer/gastritis, and anemia. The results may prove valuable in guiding the early diagnosis, management, and treatment of comorbidities in older adults living alone.
• Lee, C., Wei, S., McConnell, E., Tsumura, H., Xue, T., & Pan, W. (2024). Comorbidity patterns in older patients undergoing hip fracture surgery: a comorbidity network analysis study. Clinical Nursing Research, 33(1). doi:10.1177/10547738231209367
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  Comorbidity network analysis (CNA) is a technique in which mathematical graphs encode correlations (edges) among diseases (nodes) inferred from the disease co-occurrence data of a patient group. The present study applied this network-based approach to identifying comorbidity patterns in older patients undergoing hip fracture surgery. This was a retrospective observational cohort study using electronic health records (EHR). EHR data were extracted from the one University Health System in the southeast United States. The cohort included patients aged 65 and above who had a first-time low-energy traumatic hip fracture treated surgically between October 1, 2015 and December 31, 2018 (n = 1,171). Comorbidity includes 17 diagnoses classified by the Charlson Comorbidity Index. The CNA investigated the comorbid associations among 17 diagnoses. The association strength was quantified using the observed-to-expected ratio (OER). Several network centrality measures were used to examine the importance of nodes, namely degree, strength, closeness, and betweenness centrality. A cluster detection algorithm was employed to determine specific clusters of comorbidities. Twelve diseases were significantly interconnected in the network (OER > 1, p-value 2.5). Cerebrovascular disease, congestive heart failure, and myocardial infarction were identified as the central diseases that co-occurred with numerous other diseases. Two distinct clusters were noted, and the largest cluster comprised 10 diseases, primarily encompassing cardiometabolic and cognitive disorders. The results highlight specific patient comorbidities that could be used to guide clinical assessment, management, and targeted interventions that improve hip fracture outcomes in this patient group.
• Lee, C., Whooley, M., Niitsu, K., & Kim, W. (2024). Network motif detection in the network of inflammatory markers and depression symptoms among patients with stable coronary heart disease: insights from the Heart and Soul Study. Psychology International, 6(2), 440-453. doi:10.3390/psycholint6020027
• Lee, C., Whooley, M., Yang, Q., & Moriarity, D. (2024). How is inflammation biology truly associated with depression in patients with stable coronary heart disease?: Insights from the heart and Soul study. Brain, Behavior, and Immunity - Health, 37. doi:10.1016/j.bbih.2024.100747
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  Depression is known to be associated with inflammation among patients with established coronary heart disease (CHD), but it is unclear whether this is due to individual depression symptoms or to the broader construct of depression. We addressed this gap by using moderated non-linear factor analysis (MNLFA) to determine the extent that inflammation is associated with latent depression and/or individual symptoms in this patient group. We evaluated 1,024 outpatients with stable CHD from the baseline cross-sectional data of the Heart and Soul Study. Depression was assessed using the 9-item Patient Health Questionnaire, while inflammation was evaluated via C-reactive protein (CRP), interleukin-6 (IL-6), tumor necrosis factor-alpha (TNF-α), and monocyte chemoattractant protein-1 (MCP-1) levels. MNLFA is based on the concept of model parameter moderation with regard to individual characteristics. Using the MNLFA approach, we simultaneously tested for differences in (1) latent depression, (2) individual depression items, and (3) the factor loading of the item on latent depression as a function of inflammatory markers, with and without covariate adjustment. Higher TNF-α levels were associated with both higher levels of a latent depression factor and greater endorsement of an individual symptom (appetite changes). Increased CRP levels were significantly associated with greater appetite changes, lower concentration difficulty, and greater fatigue. Elevated IL-6 levels were only related to greater fatigue, while increased MCP-1 levels were linked to greater sleep disturbance. After adjusting for covariates, some associations became insignificant. Inflammatory markers were not consistent predictors of factor loadings. This study represents the initial step to discussing how inflammation biology is truly related to depression among patients with established CHD.
• Lee, C., Wolever, R., Min, S., Vorderstrasse, A., & Yang, Q. (2024). Network psychometrics of the 10-item perceived stress scale among patients with high cardiovascular and type 2 diabetes risk using exploratory graph analysis. Journal of Cardiovascular Nursing, 39(2). doi:10.1097/JCN.0000000000000996
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  Background No studies have explored the internal structure of the 10-item Perceived Stress Scale in patients with high cardiovascular and diabetes risk. Objective We scrutinized the dimensionality of the scale in this patient group using exploratory graph analysis, a technique within the developing field of network psychometrics. Methods Analyses were conducted on 200 primary care patients. A bootstrap version of exploratory graph analysis assessed the stability of the dimensions based on structural consistency, item stability, and network loadings. Results Exploratory graph analysis revealed a 2-dimensional structure; structural consistency of the first dimension was high (0.863), whereas that for the second was low (0.667). Items belonging to the latter dimension did not cluster consistently with each other (ie, low item stability) and were not strongly associated with any particular dimension (ie, weak network loadings). Conclusion Exploratory graph analysis offers unique outputs, making it easy to assess the dimensional integrity of scales. Further research is warranted regarding the second dimension of the Perceived Stress Scale.
• Lee, C., Yang, Q., Vorderstrasse, A., & Wolever, R. (2024). Health coaching impacts stage-specific transitions in multiple health behaviors for patients at high risk for coronary heart disease and type 2 diabetes: a multigroup latent transition analysis. Journal of Cardiovascular Nursing. doi:10.1097/JCN.0000000000001154
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  Background: Multiple behavior change interventions have gained traction in the behavioral health space. Yet, previous studies on health coaching (HC) focused on testing its effect on stages of change for individual health behaviors. Objective: The purpose of this study was to examine the effects of HC on stages of change across multiple health behavior domains among patients at high risk of coronary heart disease and type 2 diabetes. Methods: This secondary analysis of a randomized clinical trial included 200 primary care patients (mean age of 47.7 years, 49.0% women, 60.5% Whites) who completed transtheoretical model-based questionnaires related to weight reduction, exercise, healthier eating, and stress management. Multigroup latent transition analysis was used to compare the stage of change distributions and transitions over time between HC and controls at baseline, midpoint of the intervention (3 months), and postintervention (6 months). Results: Three distinct categories of behavior change were identified (“Contemplation,” “Preparation to Action,” and “Action”), and membership in these categories changed over time as a function of intervention exposure. Both groups exhibited positive transitions through stages of change from baseline to 3 months. Pronounced intervention effects emerged from 3 to 6 months, revealing larger differences in transition probabilities between the groups. In particular, HC increased patients' likelihood of transitioning from “Contemplation” to both “Preparation for Action” and “Action,” as well as from “Preparation for Action” to “Action.” The control group remained stagnant during the same period. Conclusions: Although HC produces changes across multiple behavioral domains, it was most effective for patients who were reluctant or ambivalent about changing their behaviors.
• Min, S., Lee, C., Scroggins, J., & Yang, Q. (2024). Transitions in social networks from young-old to old-old stage of life using latent transition analysis. Journal of Aging and Health, 36(1-2). doi:10.1177/08982643231177400
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  Introduction: This study aimed to identify the different types of social networks among young-old adults, and to examine the transitions in social networks as they become old-old adults. Methods: This is a secondary data analysis using the longitudinal data (N = 1092) from the National Social Life, Health, and Aging Project. Latent class analysis was conducted to identify optimal number of classes and latent transition analysis was conducted to examine the transition probabilities. Results: Young-old adults in Class 1: family-oriented, social (close, external) transitioned into Class 2: family-oriented, non-social over time. In contrast, young-old adults in Class 2: family-oriented, non-social and Class 3: less family-oriented, social (close) were less likely to transition to another class. Conclusion: Older adults engaged in less social activities over time. Older adults should be encouraged to continue their social engagement with close social network of friends and relatives, and to maintain their relationship with family members.
• Min, S., Schnall, R., Lee, C., & Topaz, M. (2024). An examination of the non-linear relationship between cognition and total hemoglobin among the cognitively normal older adults by gender. Journal of Aging and Health, 36(1-2). doi:10.1177/08982643231172230
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  Objectives: This exploratory study aimed to identify the potential non-linear relationship between hemoglobin (Hgb) and cognition among cognitively normal older adults and how this relationship differs in terms of gender in generalized additive models (GAM). Methods: This is a secondary data analysis using Wave II (2010–2011) data from the National Social Life, Health, and Aging Project. A generalized additive model was used to understand the non-linear relationship between Hgb and cognition, and to identify critical Hgb point related to cognition. Results: While both genders had a non-linear association between Hgb and cognition, the degree of non-linearity was more pronounced in male older adults with EDF value close to 2. The inflection point of 15.10 g/dL for male older adults and inflection point of 11.72 g/dL for female older adults were obtained. Conclusion: Further studies are needed to validate these results and develop precision medicine approaches to integrate these results into clinical practice.
• Min, S., Schnall, R., Lee, C., & Topaz, M. (2024). Examining racial differences in the network structure and properties of specific cognitive domains among older adults. GeroScience, 46(1). doi:10.1007/s11357-023-00912-4
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  Older adults oftentimes experience cognitive aging which leads to varying degrees of cognitive impairment. Previous studies have found that racial and ethnic disparities exist in the prevalence and severity of cognitive impairment among older adults. Yet, little is known on the relationship among specific cognitive domains and how this relationship differs between African American and White older adults. This is a secondary data analysis of Wave II (2010–2011) data from the National Social Life, Health, and Aging Project (NSHAP). A total of 2,471 older adults aged between 65 and 85 years old (African American n = 452, White n = 2019) were included. Network analysis was used to visualize and characterize the network structure and to examine network stability. Then, network comparison test was conducted to compare the network properties of the cognitive network structure between African American and White older adults. African American older adults had a lower cognitive function in all cognitive domains than White older adults. While there was no significant difference in global strength, there was a significant difference in the network structure and strength centrality measure between the two groups (p < 0.05). The invariance edge strength test found the language—visuospatial edge to be significantly stronger in African American older adults. Clinicians need to understand the different cognitive function across multiple cognitive domains between African American and White older adults and routinely offer targeted and timely cognitive assessment and management in this population.
• Min, S., Schnall, R., Lee, C., & Topaz, M. (2024). Relationship between hemoglobin and specific cognitive domain among older adults using network analysis. Aging and Mental Health. doi:10.1080/13607863.2024.2370442
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  Objectives: Hemoglobin (Hgb) is associated with cognitive function, with low and high levels of Hgb leading to impaired cerebral oxygenation and perfusion. Yet, current studies focused on understanding the association between Hgb and cognitive function without consideration for each cognitive domain. Thus, this study aims to identify and visualize potentially interactive associations between Hgb and specific cognitive domains among older adults. Method: This is a secondary data analysis using Wave II data from the National Social Life, Health, and Aging Project (NSHAP) and included 1022 older adults aged between 65 and 85 years. The network structure of three different models was estimated to understand the association between specific cognitive domains and Hgb in a mixed graphical model using the R-package ‘mgm’. Model 1 did not adjust for any covariates, Model 2 adjusted for age and gender, and Model 3 adjusted for all covariates. Results: Among all cognitive domains, the visuospatial (edge weight = 0.06–0.10) and memory domains (0.04–0.07) were associated with Hgb in all three models Though not present in Model 3, the attention domain was associated with Hgb in Model 1 and Model 2 (0.08–0.11). In addition, the predictability of Hgb was the highest (8.1%) in Model 3. Conclusion: Findings from this study suggest that cognition should be considered as a multidimensional construct, and its specific cognitive domain should be carefully assessed and managed in relation to Hgb among older adults.
• Min, S., Topaz, M., Lee, C., & Schnall, R. (2024). Racial differences in older adults’ mental health and cognitive symptomatology: identifying subgroups using multiple-group latent class analysis. Journal of Aging and Health, 36(10). doi:10.1177/08982643231212547
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  Introduction: Little is known on the potential racial differences in latent subgroup membership based on mental health and cognitive symptomatology among older adults. Methods: This is a secondary data analysis of Wave 2 data from the National Social Life, Health, and Aging Project (N = 1819). Symptoms were depression, anxiety, loneliness, happiness, and cognition. Multiple-group latent class analysis was conducted to identify latent subgroups based on mental health and cognitive symptoms and to compare these differences between race. Results: Class 1: “Severe Cognition & Mild-Moderate Mood Impaired,” Class 2: “Moderate Cognition & Mood Impaired,” and Class 3: “Mild Cognition Impaired & Healthy Mood” were identified. Black older adults were more likely to be in Class 1 while White older adults were more likely to be in Class 2 and Class 3. Discussion: Clinicians need to provide culturally-sensitive care when assessing and treating symptoms across different racial groups.
• Niitsu, K., Lee, C., & Rice, M. (2024). Interactions between serotonin transporter gene and adverse childhood experience in a generalized additive model: a pilot study. Journal of the American Psychiatric Nurses Association. doi:10.1177/10783903241255710
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  BACKGROUND: While most people experience potentially traumatic events (PTEs), including Adverse Childhood Experiences (ACEs), the stress reactions to PTEs on mental health outcomes are highly heterogeneous. Resilience is influenced by a complex biopsychosocial ecological system, including gene serotonin transporter-linked promoter region or 5-HTTLPR /rs25531 by ACEs interactions. AIMS: This pilot study investigated the gene-by-environment interactions on mental health outcomes in adults enrolled in a health care profession program using a generalized additive model (GAM). METHODS: Seventy health care college students (mean age = 27.4 years, 67.1% women) participated in this cross-sectional study. Saliva samples were collected from students to analyze 5-HTTLPR/rs25531. Participants completed the ACE Questionnaire and the Mental Health Inventory. GAMs with different interaction terms were built adjusting for age, gender, and race. The value of the effective degree of freedom (EDF) quantifies the curvature of the relationship. RESULTS: Among participants with the long allele of 5-HTTLPR/rs25531, a linear pattern was found between the total ACE score and mental health outcomes (EDF = 1). Conversely, among participants with the short allele, EDF was approximately 2, indicating a curved association suggesting that mental health worsens in individuals exposed to up to four types of ACEs. CONCLUSIONS: The impact of up to four ACEs on mental health was stronger among individuals with the short allele of 5-HTTLPR/rs25531 than those with the long allele. Although this study does not claim to provide a definite approach to analyzing gene-by-environment interactions, we offer a different perspective to explore the relationship.
• Park, J., Lee, C., Lin, L., Galvin, J., Fain, M. J., Allen, A., Park, L., & Ahn, H. (2024). Efficacy of home-based remotely supervised transcranial direct current stimulation for managing neuropsychiatric symptoms in older adults with Alzheimer’s disease and related dementias. Integrative and Complementary Therapies, 30(5). doi:https://doi.org/10.1089/ict.2024.21943.jp