ABSTRACT
Pseudomonas aeruginosa (P. aeruginosa) poses a significant threat as a nosocomial pathogen due to its robust resistance mechanisms and virulence factors. This study integrates subtractive proteomics and ensemble docking to identify and characterize essential proteins in P. aeruginosa, aiming to discover therapeutic targets and repurpose commercial existing drugs. Using subtractive proteomics, we refined the dataset to discard redundant proteins and minimize potential cross-interactions with human proteins and the microbiome proteins. We identified 12 key proteins, including a histidine kinase and members of the RND efflux pump family, known for their roles in antibiotic resistance, virulence, and antigenicity. Predictive modeling of the three-dimensional structures of these RND proteins and subsequent molecular ensemble-docking simulations led to the identification of MK-3207, R-428, and Suramin as promising inhibitor candidates. These compounds demonstrated high binding affinities and effective inhibition across multiple metrics. Further refinement using non-covalent interaction index methods provided deeper insights into the electronic effects in protein-ligand interactions, with Suramin exhibiting superior binding energies, suggesting its broad-spectrum inhibitory potential. Our findings confirm the critical role of RND efflux pumps in antibiotic resistance and suggest that MK-3207, R-428, and Suramin could be effectively repurposed to target these proteins. This approach highlights the potential of drug repurposing as a viable strategy to combat P. aeruginosa infections.
Subject(s)
Anti-Bacterial Agents , Bacterial Proteins , Drug Repositioning , Molecular Docking Simulation , Proteome , Proteomics , Pseudomonas aeruginosa , Pseudomonas aeruginosa/drug effects , Pseudomonas aeruginosa/metabolism , Bacterial Proteins/metabolism , Bacterial Proteins/chemistry , Bacterial Proteins/antagonists & inhibitors , Proteomics/methods , Proteome/metabolism , Anti-Bacterial Agents/pharmacology , Anti-Bacterial Agents/chemistry , Suramin/pharmacology , Suramin/chemistry , HumansABSTRACT
Tuskegee, in Macon County, Alabama, has played an important role in Alabama's midwifery legacy and was home to 2 different midwifery education programs from the 1920s through the 1940s. In response to a 1918 state law requiring midwives to pass an examination to receive a practice permit in their county, stakeholders developed a four-week course for Black Alabamian midwives on the grounds of Tuskegee Institute at the John A. Andrew Memorial Hospital. In the 1940s, in the same location on the grounds of Tuskegee Institute, the Tuskegee School of Nurse-Midwifery educated Black nurse-midwives to improve Black maternal and neonatal outcomes in the South.
ABSTRACT
The breast microbiome presents a diverse microbial community that could affects health and disease states, in the context of breast cancer. Sequencing technologies have allowed describing the diversity and abundance of microbial communities among individuals. The complex tumoral microenvironment that includes the microbial composition could influence tumor growth. The imbalance of diversity and abundance inside the microbial community, known as dysbiosis plays a crucial role in this context. One the most prevalent bacterial genera described in breast invasive carcinoma are Bacillus, Pseudomonas, Brevibacillus, Mycobacterium, Thermoviga, Acinetobacter, Corynebacterium, Paenibacillus, Ensifer, and Bacteroides. Paenibacills genus shows a relation with patient survival. When the Paenibacills genus increases its abundance in patients with breast cancer, the survival probability decreases. Within this dysbiotic environment, various bacterial metabolites could play a pivotal role in the progression and modulation of breast cancer. Key bacterial metabolites, such as cadaverine, lipopolysaccharides (LPS), and trimethylamine N-oxide (TMAO), have been found to exhibit potential interactions within breast tissue microenvironments. Understanding the intricate relationships between dysbiosis and these metabolites in breast cancer may open new avenues for diagnostic biomarkers and therapeutic targets. Further research is essential to unravel the specific roles and mechanisms of these microbial metabolites in breast cancer progression.
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OBJECTIVE: Exposure to neighborhood violence may have negative implications for adults' cognitive functioning, but the ecological sensitivity of these effects has yet to be determined. We first evaluated the link between exposure to neighborhood violence and two latent constructs of cognitive function that incorporated laboratory-based and ambulatory, smartphone-based, cognitive assessments. Second, we examined whether the effect of exposure to violence was stronger for ambulatory assessments compared to in-lab assessments. METHODS: We used data from 256 urban-dwelling adults between 25 and 65 years old (M = 46.26, SD = 11.07); 63.18% non-Hispanic Black, 9.21% non-Hispanic White, 18.41% Hispanic White, 5.02% Hispanic Black, and 4.18% other. Participants completed baseline surveys on neighborhood exposures, cognitive assessments in a laboratory/research office, and ambulatory smartphone-based cognitive assessments five-times a day for 14 days. RESULTS: Exposure to neighborhood violence was associated with poorer performance in a latent working memory construct that incorporated in-lab and ambulatory assessments, but was not associated with the perceptual speed construct. The effect of exposure to neighborhood violence on the working memory construct was explained by its effect on the ambulatory working memory task and not by the in-lab cognitive assessments. CONCLUSION: This study shows the negative effect that exposure to neighborhood violence may have on everyday working memory performance in urban-dwelling adults in midlife. Results highlight the need for more research to determine the sensitivity of ambulatory assessments to quantify the effects of neighborhood violence on cognitive function.
Subject(s)
Cognition , Exposure to Violence , Residence Characteristics , Humans , Male , Female , Middle Aged , Adult , Residence Characteristics/statistics & numerical data , Exposure to Violence/psychology , Exposure to Violence/statistics & numerical data , Aged , Task Performance and Analysis , Urban Population/statistics & numerical data , Violence/psychology , Violence/statistics & numerical data , Memory, Short-TermABSTRACT
The present study examined early socioeconomic status (SES) and neighborhood disadvantage (ND) as independent predictors of antisocial behavior (ASB) and addressed the etiology of the associations (i.e., genes versus the environment) using a longitudinal adoption design. Prospective data from the Colorado Adoption Project (435 adoptees, 598 nonadopted children, 526 biological grandparents of adoptees, 481 adoptive parents, and 617 nonadoptive parents including biological parents of unrelated siblings of adoptees) were examined. SES and ND were assessed during infancy and ASB was evaluated from ages four through 16 using parent and teacher report. Associations between predictors and ASB were compared across adoptive and nonadoptive families and sex. Early SES was a nominally significant, independent predictor of antisocial ASB, such that lower SES predicted higher levels of ASB in nonadoptive families only. ND was not associated with ASB. Associations were consistent across aggression and delinquency, and neither SES nor ND was associated with change in ASB over time. Nominally significant associations did not remain significant after controlling for multiple testing. As such, despite nonsignificant differences in associations across sex or adoptive status, we were unable to make definitive conclusions regarding the genetic versus environmental etiology of or sex differences in the influence of SES and ND on ASB. Despite inconclusive findings, in nonadoptees, results were consistent-in effect size and direction-with previous studies in the literature indicating that lower SES is associated with increased risk for ASB.
Subject(s)
Adoption , Social Class , Humans , Male , Female , Longitudinal Studies , Child , Adolescent , Child, Preschool , Adoption/psychology , Antisocial Personality Disorder/epidemiology , Antisocial Personality Disorder/psychology , Neighborhood Characteristics , Colorado/epidemiology , Prospective Studies , Child, Adopted/psychology , Residence CharacteristicsABSTRACT
Urease, a pivotal enzyme in nitrogen metabolism, plays a crucial role in various microorganisms, including the pathogenic Helicobacter pylori. Inhibiting urease activity offers a promising approach to combating infections and associated ailments, such as chronic kidney diseases and gastric cancer. However, identifying potent urease inhibitors remains challenging due to resistance issues that hinder traditional approaches. Recently, machine learning (ML)-based models have demonstrated the ability to predict the bioactivity of molecules rapidly and effectively. In this study, we present ML models designed to predict urease inhibitors by leveraging essential physicochemical properties. The methodological approach involved constructing a dataset of urease inhibitors through an extensive literature search. Subsequently, these inhibitors were characterized based on physicochemical properties calculations. An exploratory data analysis was then conducted to identify and analyze critical features. Ultimately, 252 classification models were trained, utilizing a combination of seven ML algorithms, three attribute selection methods, and six different strategies for categorizing inhibitory activity. The investigation unveiled discernible trends distinguishing urease inhibitors from non-inhibitors. This differentiation enabled the identification of essential features that are crucial for precise classification. Through a comprehensive comparison of ML algorithms, tree-based methods like random forest, decision tree, and XGBoost exhibited superior performance. Additionally, incorporating the "chemical family type" attribute significantly enhanced model accuracy. Strategies involving a gray-zone categorization demonstrated marked improvements in predictive precision. This research underscores the transformative potential of ML in predicting urease inhibitors. The meticulous methodology outlined herein offers actionable insights for developing robust predictive models within biochemical systems.
Subject(s)
Enzyme Inhibitors , Machine Learning , Urease , Urease/antagonists & inhibitors , Urease/chemistry , Urease/metabolism , Enzyme Inhibitors/chemistry , Enzyme Inhibitors/pharmacology , Helicobacter pylori/enzymology , Helicobacter pylori/drug effects , Algorithms , HumansABSTRACT
Helicobacter pylori (Hp) infections pose a global health challenge demanding innovative therapeutic strategies by which to eradicate them. Urease, a key Hp virulence factor hydrolyzes urea, facilitating bacterial survival in the acidic gastric environment. In this study, a multi-methodological approach combining pharmacophore- and structure-based virtual screening, molecular dynamics simulations, and MM-GBSA calculations was employed to identify novel inhibitors for Hp urease (HpU). A refined dataset of 8,271,505 small molecules from the ZINC15 database underwent pharmacokinetic and physicochemical filtering, resulting in 16% of compounds for pharmacophore-based virtual screening. Molecular docking simulations were performed in successive stages, utilizing HTVS, SP, and XP algorithms. Subsequent energetic re-scoring with MM-GBSA identified promising candidates interacting with distinct urease variants. Lys219, a residue critical for urea catalysis at the urease binding site, can manifest in two forms, neutral (LYN) or carbamylated (KCX). Notably, the evaluated molecules demonstrated different interaction and energetic patterns in both protein variants. Further evaluation through ADMET predictions highlighted compounds with favorable pharmacological profiles, leading to the identification of 15 candidates. Molecular dynamics simulations revealed comparable structural stability to the control DJM, with candidates 5, 8 and 12 (CA5, CA8, and CA12, respectively) exhibiting the lowest binding free energies. These inhibitors suggest a chelating capacity that is crucial for urease inhibition. The analysis underscores the potential of CA5, CA8, and CA12 as novel HpU inhibitors. Finally, we compare our candidates with the chemical space of urease inhibitors finding physicochemical similarities with potent agents such as thiourea.
Subject(s)
Helicobacter pylori , Helicobacter pylori/metabolism , Urease/metabolism , Molecular Dynamics Simulation , Molecular Docking Simulation , Urea/pharmacologyABSTRACT
Weight bias toward patients in larger bodies is pervasive among health care providers and can negatively influence provider-patient communication, as well as patients' behavior and health outcomes. Weight bias has historical roots that perpetuate thinness and Whiteness as the cultural norm. Although weight bias remains socially acceptable in US culture, contributing factors to an individual's body size are complex and multifactorial. Providers and health care systems also consistently use body mass index (BMI) as an indicator of health status, despite its limitations and harmful effects in the clinical setting. This state of the science review presents 8 evidence-based strategies that demonstrate how to mitigate harm from weight bias and improve quality of care and health outcomes for patients living in larger bodies. Person-centered approaches to care include (1) eliminating clinical recommendations to lose weight; (2) shifting from a focus on weight to health; (3) implementing a size and weight-inclusive approach; (4) engaging in weight bias self-evaluation; (5) creating a welcoming environment for patients of all sizes; (6) seeking permission and learning the patient's story; (7) using weight-inclusive language; and (8) re-evaluating clinical guidelines and policies based on BMI. Midwives and other health care providers may benefit from training that re-imagines the delivery of health care to patients in larger bodies.
Subject(s)
Weight Prejudice , Humans , Body Mass IndexABSTRACT
OBJECTIVES: Greater neighborhood cohesion is associated with better cognitive function in adulthood and may serve as a protective factor against cognitive impairment and decline. We build on prior work by examining the effects of perceived neighborhood cohesion across the life course on level and change in cognitive function in adulthood. METHODS: Utilizing longitudinal data from the Health and Retirement Study (1998-2016) and its Life History Mail Survey, we leveraged data from 3,599 study participants (baseline age: 51-89) who participated in up to 10 waves. Respondents provided retrospective ratings of neighborhood cohesion at childhood (age 10), young adulthood (age at the first full-time job), early midlife (age 40), and concurrently at baseline (i.e., late midlife/adulthood); they completed the modified version of the Telephone Interview for Cognitive Status. We fit a univariate latent growth curve model of change in cognitive function across waves and tested whether neighborhood cohesion during each recollected life stage predicted level and change in cognitive function. RESULTS: Greater neighborhood cohesion during childhood and late midlife/adulthood each predicted higher cognitive function at baseline but not the rate of cognitive decline. The final model showed that greater neighborhood cohesion in childhood and in late midlife/adulthood remained significantly associated with higher baseline cognitive function, even after accounting for one another. DISCUSSION: Findings provide insight into life-course neighborhood contextual influences on cognitive aging. Our results emphasize the need for more research to understand the life-course dynamics between neighborhood environments and cognitive aging.
Subject(s)
Cognitive Aging , Humans , Young Adult , Adult , Aged , Aged, 80 and over , Retrospective Studies , Life Change Events , Residence Characteristics , Cognition , Aging/psychologyABSTRACT
BACKGROUND: . Although prior studies have examined the associations between neighborhood characteristics and cognitive health, little is known about whether local food environments, which are critical for individuals' daily living, are associated with late-life cognition. Further, little is known about how local environments may shape individuals' health-related behaviors and impact cognitive health. The aim of this study is to examine whether objective and subjective measures of healthy food availability are associated with ambulatory cognitive performance and whether behavioral and cardiovascular factors mediate these associations among urban older adults. METHODS: . The sample consisted of systematically recruited, community-dwelling older adults (N = 315, mean age = 77.5, range = 70-91) from the Einstein Aging Study. Objective availability of healthy foods was defined as density of healthy food stores. Subjective availability of healthy foods and fruit/vegetable consumption were assessed using self-reported questionnaires. Cognitive performance was assessed using smartphone-administered cognitive tasks that measured processing speed, short-term memory binding, and spatial working memory performance 6 times a day for 14 days. RESULTS: . Results from multilevel models showed that subjective availability of healthy foods, but not objective food environments, was associated with better processing speed (estimate= -0.176, p = .003) and more accurate memory binding performance (estimate = 0.042, p = .012). Further, 14~16% of the effects of subjective availability of healthy foods on cognition were mediated through fruit and vegetable consumption. CONCLUSIONS: . Local food environments seem to be important for individuals' dietary behavior and cognitive health. Specifically, subjective measures of food environments may better reflect individuals' experiences regarding their local food environments not captured by objective measures. Future policy and intervention strategies will need to include both objective and subjective food environment measures in identifying impactful target for intervention and evaluating effectiveness of policy changes.
Subject(s)
Fruit , Vegetables , Humans , Aged , Access to Healthy Foods , Cognition , Health BehaviorABSTRACT
OBJECTIVES: Cognitive control predicts functional independence and cognitive health outcomes, but is yet to be known the extent to which social stress, like discrimination, may diminish cognitive control capacities in Mexican-origin women. We evaluated the prospective associations between everyday and ethnic discrimination on cognitive control and examined the mediating effects of depressive symptoms on these links. We further examined the extent to which associations varied by age and financial strain. METHODS: We used data from 596 Mexican-origin women (average age = 38.89, standard deviation = 5.74) who participated in a 3-wave longitudinal study spanning 8 years (from 2012 to 2020). Participants completed measures of everyday and ethnic discrimination at Wave 1, depressive symptoms in Waves 1 and 2, and completed computer-based tasks of cognitive control at Wave 3. Self-reported assessments of financial strain were completed at Wave 2. Moderated mediation structural equation models were implemented to test hypotheses. RESULTS: Depressive symptoms significantly mediated the prospective association between everyday/ethnic discrimination to cognitive control. Higher levels of everyday and ethnic discrimination at baseline were associated with more depressive symptoms at Wave 2, which were then related to poorer cognitive control (i.e., longer reaction time in congruent and/or incongruent trials) at Wave 3. There was no significant moderation of age. Among those with low financial strain, higher levels of everyday discrimination were related to faster response times. DISCUSSION: Results revealed the long-term consequences of experiences with discrimination on cognitive control that operate through increased depressive symptoms and that may have some subtle differential effects across levels of financial strain.
Subject(s)
Depression , Racism , Humans , Female , Longitudinal Studies , Depression/psychology , Racism/psychology , Cross-Sectional Studies , CognitionABSTRACT
In light of the growing bacterial resistance to antibiotics and in the absence of the development of new antimicrobial agents, numerous antimicrobial delivery systems over the past decades have been developed with the aim to provide new alternatives to the antimicrobial treatment of infections. However, there are few studies that focus on the development of a rational design that is accurate based on a set of theoretical-computational methods that permit the prediction and the understanding of hydrogels regarding their interaction with cationic antimicrobial peptides (cAMPs) as potential sustained and localized delivery nanoplatforms of cAMP. To this aim, we employed docking and Molecular Dynamics simulations (MDs) that allowed us to propose a rational selection of hydrogel candidates based on the propensity to form intermolecular interactions with two types of cAMPs (MP-L and NCP-3a). For the design of the hydrogels, specific building blocks were considered, named monomers (MN), co-monomers (CM), and cross-linkers (CL). These building blocks were ranked by considering the interaction with two peptides (MP-L and NCP-3a) as receptors. The better proposed hydrogel candidates were composed of MN3-CM7-CL1 and MN4-CM5-CL1 termed HG1 and HG2, respectively. The results obtained by MDs show that the biggest differences between the hydrogels are in the CM, where HG2 has two carboxylic acids that allow the forming of greater amounts of hydrogen bonds (HBs) and salt bridges (SBs) with both cAMPs. Therefore, using theoretical-computational methods allowed for the obtaining of the best virtual hydrogel candidates according to affinity with the specific cAMP. In conclusion, this study showed that HG2 is the better candidate for future in vitro or in vivo experiments due to its possible capacity as a depot system and its potential sustained and localized delivery system of cAMP.
ABSTRACT
Latinx adults with both cognitive dysfunction and type 2 diabetes mellitus (T2DM) are significantly more likely than Latinx adults with diabetes alone to have complications such as cardiovascular disease. Glucose variability may be a risk for dementia, but the course of glucose variability in the time before a dementia diagnosis for Latinx adults with T2DM has not been examined. We used a 10-year retrospective cohort of medical records of Latinx patients with T2DM who had at least one use of a continuous glucose monitor. The objective was to examine how glucose variability was associated with future dementia diagnoses. A total of 116 charts were included. Mean of daily differences and mean amplitude of glycemic excursions were more strongly associated with dementia diagnoses than other variability indices (p < .01). Understanding the relationships between cognitive function, glucose variability, and barriers to health care can translate into improved interventions to enhance diabetes care.
Subject(s)
Dementia , Diabetes Mellitus, Type 2 , Humans , Adult , Diabetes Mellitus, Type 2/complications , Diabetes Mellitus, Type 2/psychology , Retrospective Studies , Glucose , Incidence , Glycated Hemoglobin , Blood Glucose , Dementia/epidemiology , Hispanic or LatinoABSTRACT
OBJECTIVES: To evaluate temporal dynamics between loneliness and both objective and subjective health (i.e. functional impairment and self-rated health) in mid- to late-adulthood. METHOD: We applied bivariate dual-change-score models to longitudinal data from 3 Swedish twin studies (N = 1,939) to explore dynamic associations between loneliness and health across 3 age ranges (50-69, 70-81, and 82+ years) to investigate whether associations between loneliness and health change with age due to increasing incidence of chronic health conditions and bereavement. RESULTS: Results showed bidirectional associations between loneliness and both objective and subjective health, with adverse impacts of loneliness observed on subsequent subjective and objective health beginning at age 70. Associations between health and subsequent loneliness were observed after age 82 and varied for subjective and objective health, with subjective health associated with less loneliness and objective health associated with greater loneliness. CONCLUSIONS: Our results indicate dynamic associations between loneliness and health with age in mid- to late-adulthood, with earlier impacts of loneliness on health and later impacts of health on loneliness that vary for objective and subjective measures of health. These findings suggest impacts of health on loneliness may arise later in life when worsening health or mobility interfere with social interaction.
Subject(s)
Diagnostic Self Evaluation , Loneliness , Humans , Adult , Aged , Aged, 80 and over , Longitudinal Studies , Social InteractionABSTRACT
OBJECTIVES: Hispanic/Latinx adults are at increased risk for cognitive impairment, and it is critically important to identify modifiable risk factors for cognitive impairment in this population. We addressed two key questions: (1) How does perceived discrimination change across middle adulthood? And, (2) how are discrimination and the trajectory of discrimination associated with cognitive function? METHODS: We used data from 1,110 Mexican-origin adults between 26 and 62 years old (63% female; 85% born in Mexico). Participants completed a perceived ethnic discrimination scale five times across 12 years and completed cognitive assessments in the last wave, which were composited into a measure of overall cognitive function. We used latent growth curve models to estimate the longitudinal trajectory of perceived ethnic discrimination and growth mixture models to identify sub-groups of change trajectories. We evaluated whether patterns of perceived discrimination trajectories, baseline, intermediary, and concurrent discrimination predicted cognitive function at the last wave. RESULTS: Perceived ethnic discrimination decreased over time on average. Significant individual differences in within-person change revealed two change trajectory classes: Stable Low and High Declining. The Stable Low class had better cognitive performance compared to the High Declining class, but this effect was not robust to educational attainment. Perceived discrimination at the last wave was associated with worse cognitive function, and this effect remained after accounting for covariates. CONCLUSIONS: This study is among the first to evaluate changes in perceived ethnic discrimination in a sample of Mexican-origin adults and their associations with cognitive function. The results highlight the need for more research to better understand the role of discrimination and other social stressors on cognitive health outcomes.
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OBJECTIVES: Identifying sociocultural correlates of neurocognitive dysfunction among Hispanics/Latinos, and their underlying biological pathways, is crucial for understanding disparities in Alzheimer's disease and related dementias. We examined cross-sectional associations between stress and neurocognition, and the role that metabolic syndrome (MetS) and systemic inflammation might play in these associations. METHOD: Participants included 3,045 adults aged 45-75 (56% female, education 0-20+ years, 86% Spanish-speaking, 23% U.S.-born), enrolled in the Hispanic Community Health Study/Study of Latinos and its Sociocultural Ancillary Study. Global neurocognition was the primary outcome and operationalized as the average of the z scores of measures of learning and memory, word fluency, and processing speed. Stress measures included self-report assessments of stress appraisal (perceived and acculturative stress) and exposure to chronic and traumatic stressors. MetS was defined via established criteria including waist circumference, high blood pressure, elevated triglycerides, fasting plasma glucose, and high levels of high-density lipoprotein cholesterol. Systemic inflammation was represented by high-sensitivity C-reactive protein (hs-CRP). RESULTS: Separate survey multivariable linear regression models adjusting for covariates showed that higher perceived (b = -0.004, SE = 0.002, p < .05) and acculturative stress (b = -0.004, SE = 0.001, p < .0001) were significantly associated with worse global neurocognition, while lifetime exposure to traumatic stressors was associated with better global neurocognition (b = 0.034, SE = 0.009, p < .001). Neither MetS nor hs-CRP were notable pathways in the association between stress and neurocognition; rather, they were both independently associated with worse neurocognition in models including stress measures (ps < .05). DISCUSSION: These cross-sectional analyses suggest that stress appraisal, MetS, and systemic inflammation may be targets to reduce neurocognitive dysfunction among Hispanics/Latinos.
Subject(s)
Metabolic Syndrome , C-Reactive Protein , Cross-Sectional Studies , Female , Hispanic or Latino , Humans , Inflammation , Male , Risk Factors , Self ReportSubject(s)
Aging , Dementia , Geroscience , Aging/psychology , COVID-19/prevention & control , Caregivers/psychology , Dementia/therapy , HumansABSTRACT
OBJECTIVES: The purpose of this study was to evaluate the hypothesis that chronic and acculturative stress would be negatively associated with neurocognitive function among middle aged to older Hispanics/Latinos. METHOD: Our analytic sample consisted of 3,265 participants (mean age = 56.7 (±0.24)) from the Hispanic Community Health Study/Study of Latinos who participated in its Sociocultural Ancillary Study. During the baseline phase of this project, participants were assessed on multiple domains of neurocognitive function, and completed self-report measures of chronic and acculturative stress. RESULTS: Each standard deviation increase in chronic stress was associated with lower performance in a verbal learning task (B = -.17, 95% CI [-.32, -.01]); this association was no longer significant after adjusting for mental and physical health symptoms, including depression and anxiety symptoms, and cardiovascular health. A standard deviation increase in acculturative stress was associated with poorer performance in all cognitive measures (Bs range = -.13 to -1.03). Associations of acculturation stress with psychomotor speed, verbal learning, and word fluency remained significant after adjusting for mental and physical health symptoms. DISCUSSION: Our results suggest that mental and physical health may help explain some cross-sectional associations between stress and cognition and highlight the need to examine culture-specific psychosocial stressors to better understand the context of psychosocial risk factors for neurocognitive performance.
Subject(s)
Acculturation , Cognition , Mental Status and Dementia Tests/statistics & numerical data , Psychology , Stress, Psychological , Female , Health Status Disparities , Hispanic or Latino/psychology , Humans , Male , Middle Aged , Psychomotor Performance , Residence Characteristics , Risk Factors , Self Report/statistics & numerical data , Stress, Psychological/ethnology , Stress, Psychological/etiology , Stress, Psychological/psychology , United States/epidemiology , Verbal LearningABSTRACT
Little research has examined how the link between discrimination and cognitive health varies by where people live. This study investigates how living in non-urban versus urban areas in different regions in the United States moderates the discrimination-cognitive health link among older non-Hispanic Blacks. Data are from the 2012 and 2014 waves of the Health and Retirement Study (HRS; N=2,347). Regression analyses indicate that experiencing more everyday discrimination is significantly associated with lower episodic memory when living in urban areas. Among non-Hispanic Blacks, the discrimination-episodic memory link does not significantly vary across U.S. regional contexts. Findings highlight variation in the association between everyday discrimination and cognitive health by where older non-Hispanic Blacks live. Results suggest the importance of socio-environmental factors in shaping how stressful experiences such as discrimination are linked to cognitive health in later life.
ABSTRACT
The objective of this study was to evaluate the association between perceived neighborhood stressors, encompassing negative perceived neighborhood characteristics, and specific cognitive abilities in adulthood. We conducted a coordinated analysis across three studies of adults in the United States and found that perceived neighborhood stressors were consistently associated with poorer performance on attention-demanding cognitive tasks. We specifically found that perceived neighborhood stressors were associated with lower performance in spatial abilities, working memory, and executive function but not perceptual speed, and that the effect was most consistent for lower perceived neighborhood safety followed by lower perceived aesthetic quality, greater perceived neighborhood crime, and lower perceived neighborhood cohesion. These results highlight the importance of the psychosocial neighborhood context for cognitive health in adulthood.