Mild Cognitive Impairment Prevalence and Associated Risk Factor Frequency Among Mexican-origin Adults in Southern Arizona

Mild Cognitive Impairment Prevalence and Associated Risk Factor Frequency Among Mexican-origin Adults in Southern Arizona | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Mild Cognitive Impairment Prevalence and Associated Risk Factor Frequency Among Mexican-origin Adults in Southern Arizona Shannon Lindemer, Adriana Maldonado, Estefania Ochoa-Mora, Edgar Villavicencio, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8414548/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Limited research exists among Mexican-origin populations related to Mild Cognitive Impairment (MCI) and Alzheimer’s Disease risk factors in community-based settings. Objective This study aims to characterize the prevalence of MCI using the Montreal Cognitive Assessment in Spanish (MoCA-S) among Mexican-origin adults in Southern Arizona while identifying risk factors associated with MCI in this population. Methods A community-based sample of 194 Mexican-origin adults (women = 134; men = 56; mean age = 51.64 ± 12.3 years) in Southern Arizona participated in the study. The MoCA-S was administered and interpreted based on established cutoffs for cognitive function. A generalized linear model was fitted to explore the predictors of MCI while adjusting for sociodemographic, cardiometabolic, and mental health characteristics. Results The mean MoCA-S score was 21.6 ± 3.9, with 30 participants (15.46%) identified with mild to severe cognitive impairment. The adjusted model indicated that participants with a college degree or greater had higher MoCA-S scores compared to those with less than a 6th -grade level education (β = 3.67, 95% CI = 1.61, 5.72). No significant differences in MoCA-S scores were observed for age, sex, years in the U. S., body mass index, metabolic dysfunction-associated steatotic liver disease status, blood pressure, diabetes status, perceived stress, and smoking status (p > 0.05). Conclusion This study highlights the unique cognitive health challenges and opportunities within Mexican-origin communities in Southern Arizona. Addressing key factors, such as improving educational strategies while leveraging culturally sensitive screening tools, can support public health efforts to mitigate the burden of MCI in this high-risk population. Alzheimer’s disease cardiometabolic syndrome mental health Hispanic mild cognitive impairment Montreal Cognitive Assessment (MoCA) Introduction Mild Cognitive Impairment (MCI) is distinguished by a decrease in one or more cognitive domains[ 1 ]. While previous work suggests the existence of a strong association between MCI risk factors (e.g., obesity, cardiovascular disease (CVD), and type 2 diabetes (T2D)) and the rate of progression of MCI; the majority of these findings are derived from non-Hispanic white (NHW) populations. This is a significant gap in the MCI literature, as nearly 18% of the United States (U.S.) population is Hispanic [ 2 ]. By 2060, the number of people in this group aged 65 and older is expected to reach 20 million, with rates of MCI and Alzheimer's disease (AD) increasing six-fold [ 3 ]. This is particularly relevant for Mexican-origin adults in the U.S., who comprise approximately 60% of the Hispanic population and experience a disproportionate burden of modifiable risk factors for MCI, such as CVD and T2D [ 4 – 7 ]. In addition, studies indicate that Mexican-origin adults are often diagnosed with MCI, dementia, and AD at more advanced stages and younger ages compared to other Hispanic subgroups and NHWs [ 8 ]. Therefore, efforts to characterize risk factors associated with MCI among Mexican-origin adults are necessary to reduce the burden of this disease for this high-risk community. In Hispanic populations, prevalent modifiable risk factors increase the likelihood of developing MCI and progressing to dementia through cardiometabolic, vascular, and psychological pathways [ 9 – 12 ]. These conditions can interact and exacerbate each other, worsening cognitive health outcomes. For instance, obesity heightens the risk of developing T2D, CVD (e.g., hypertension), and metabolic dysfunction-associated steatotic liver disease (MASLD), which increases MCI risk through vascular dysfunction and metabolic abnormalities [ 13 , 14 ]. Moreover, poor glycemic control links T2D to MCI via vascular complications in the brain and accelerates cognitive decline by up to seven years among Hispanic adults [ 15 , 16 ]. Depression exacerbates MCI risk, particularly for individuals who experience chronic stress [ 17 , 18 ]. Lastly, additional risk factors, including age, sex, and educational attainment, often linked to socioeconomic disparities, elevate the risk of MCI for Mexican-origin adults [ 19 , 20 ]. Mexican-origin adults’ risk for MCI is further compounded by sociocultural factors such as limited access to healthcare, perceptions of MCI risk, and the ability to receive culturally congruent care [ 21 ]. In fact, the early screening and detection of cognitive decline requires comprehensive neuropsychological testing, the most reliable clinical method; however, brief medical appointments and long waits for testing pose significant challenges [ 22 ]. There are also many practical challenges to conducting MCI testing among English and Spanish-speaking Hispanics, including the use of appropriate cognitive assessment tools with normative cognitive data [ 23 ]. Detecting MCI, particularly in preclinical stages, is crucial to mitigate the burden of this disease among Mexican-origin adults and to reduce progression to AD [ 24 ]. The current study aimed to characterize the prevalence of MCI using the Spanish version of the Montreal Cognitive Assessment (MoCA-S) among Mexican-origin adults in Southern Arizona and to identify risk factors associated with MCI in this population. Specifically, we evaluated the impact of sociodemographic characteristics (e.g., educational attainment), cardiometabolic (e.g., hypertension), and mental health (e.g., depression) risk factors on cognitive function among this vulnerable population. Methods Study Design, Sample, and Data Collection Procedures A community-based cross-sectional sample of 194 Mexican-origin adults residing in the Southern Arizona U.S./Mexico border region was recruited. Eligible participants self-identified as foreign-born Mexican-origin adults who were at least 18 years of age, able to provide informed consent, and proficient in speaking, reading, and writing in either English or Spanish. Participants were recruited through three primary strategies: face-to-face interactions during community outreach events (e.g., local swap meet/flea market and Mexican Consulate), distribution of study-related flyers, and word of mouth. Data collection occurred between May 2023 and February 2024. Individuals expressing interest in the study completed a screening questionnaire at recruitment events to determine eligibility. Those who met the eligibility criteria were invited to the University of Arizona Collaboratory for Metabolic Disease Prevention and Treatment to complete a 90-minute in-person visit which consisted of written informed consent, cognitive assessment, anthropometric measures, blood pressure, cardiometabolic blood values, FibroScan®, and self-reported questionnaires. Study visits and self-reported questionnaires were completed in either Spanish or English, depending on the participants’ preferred language. After completing all data collection procedures, participants were compensated $ 50 for their time. Ethical approval for all study materials and research protocol was obtained from the University of Arizona’s Institutional Review Board under protocol STUDY00001145. Measures Montreal Cognitive Assessment in Spanish Cognitive function was evaluated using the validated Montreal Cognitive Assessment in Spanish v8.1 (MoCA-S), a valid and reliable instrument for MCI and dementia screening in Mexican-origin populations [ 25 ]. The MoCA-S was administered by research staff who were formally trained in its administration by a professional certified psychometrist, ensuring standardized administration. Scores range from 0 to 30, with higher scores indicating better cognitive performance. Participants with less than 12 years of education received an additional point to adjust for educational disparities. We followed established MoCA interpretation guidelines, categorizing scores as normal (26–30), mild (18–25), moderate (10–17), and severe (< 10), consistent with validation studies in Spanish-speaking populations [ 25 ]. Due to small cell sizes, MoCA-S scores were dichotomized as “normal to mild MCI” and “moderate to severe MCI.” Cardiometabolic Risk Factors Body Mass Index (BMI). Using a wall-mounted stadiometer (ShorrBoard®), participants’ height was measured without shoes, twice to the nearest 0.1 cm. Without shoes and in participants’ street clothes, participants’ weight was measured twice on a calibrated digital scale (Seca 8760) to the nearest 0.1 kg.[ 26 ] BMI was computed by dividing the average body weight in kilograms by squared average height in meters (kg/m 2 ) and classified into standard categories: healthy weight (18.5 to 24.9 kg/m 2 ), overweight (25 to 29.9 kg/m 2 ), and obesity (≥ 30 kg/m 2 ). Blood Pressure. A digital blood pressure monitor (Omron HEM-907XL) was used to measure systolic (SBP) and diastolic blood pressure (DBP).[ 26 ] Measurements followed the National Health and Nutrition Examination Survey protocol: two seated blood pressure readings were obtained after a rest period of at least five minutes, with a third reading taken if there was notable variability between the first two. The average of the valid readings was used in all analyses to ensure accuracy and reliability [ 27 ]. Participants’ blood pressure readings were classified as normal (SBP < 120 mmHg and DBP < 80mmHg), elevated (120–129 mmHg and DBP < 80mmHg), stage 1 hypertension (130–139 mmHg or DBP 80–89 mmHg), and stage 2 hypertension (≥ 140 mmHg or DBP ≥ 90 mmHg) [ 28 ]. These categories were selected in accordance with the 2017 American College of Cardiology/American Heart Association (ACC/AHA) clinical practice guidelines for the prevention, detection, evaluation, and management of high blood pressure in adults, to ensure consistency with established standards and facilitate comparability with other studies [ 28 ]. Metabolic Dysfunction-Associated Steatotic Liver Disease Status. MASLD was identified via vibration-controlled transient elastography (FibroScan® 430 MINI+). A continuous attenuation parameter (CAP) score of ≥ 288 dB/m indicated MASLD status [ 29 ]. Scans were considered complete and valid if participants fasted for at least three hours, and a total of 10 liver stiffness measurement (LSM) measures were obtained with an interquartile range (IQR)/median value of less or equal than 30% [ 30 ]. Type 2 Diabetes Status. Hemoglobin A1C (HbA1C) levels were determined via fasting blood samples analyzed by a commercial laboratory. Participants’ HbA1C levels were classified as normal ( 6.5%) [ 31 ]. Mental Health Risk Factors Depressive Symptoms. The Center for Epidemiological Studies-Depression (CES-D) scale, a 20-item self-report, was used to assess depressive symptoms experienced in the past week [ 32 ]. Scores range from 0 to 60, with a cutoff of ≥ 16 indicating risk for clinical depression. Perceived Stress. Levels of perceived stress were measured using the Perceived Stress Scale (PSS-10), a valid and reliable measure in Hispanic populations [ 33 ]. The four positively worded items (Items 4, 5, 7, 8) were reversed scored, and a total score was computed by adding all 10 items ranging from 0 to 40. Perceived stress levels were categorized as low stress (≤ 13), moderate stress (14–26), and elevated stress (≥ 27). Sociodemographic Characteristics and Health-related Behaviors Descriptive variables, including age, sex, educational attainment, time of residence in the U.S., employment status, and smoking status, were included as covariates in the analyses of the current study. Statistical Analyses A complete case data analysis was conducted using SAS software [ 34 ]. Summary statistics were used to describe the analytical sample stratified by cognitive function status. Generalized linear models using PROC GLM, were used to estimate unadjusted and adjusted mean differences in cognitive functioning scores (MoCA-S) for participants’ cardiometabolic risk factors (i.e., BMI, blood pressure, MASLD, and T2D status), mental health risk factors (i.e., depressive symptoms and perceived stress), and sociodemographic characteristics and health variables (i.e., age, sex, educational attainment, and smoking status). As acculturation has been associated with cognitive performance among Hispanics[ 35 ], the general linear models adjusted for years in the U.S., a proxy measure of acculturation. Two-sided p-values of < 0.05 were considered statistically significant. Results Participant Characteristics Of the total sample, 15.5% (n = 30) of participants were identified with moderate to severe MCI, which includes 8 participants between 18 and 49 years (26.7%), 11 participants between 59 and 59 years (36.7%) and 11 participants aged 60 years and over (36.7%). Educational attainment varied significantly between the groups (p < 0.001). Individuals in the Moderate to Severe MCI group were more likely to have completed only grades 1–6 (42.86%) compared to 12.96% in the Normal to Mild MCI group. Conversely, participants with a college degree or higher were less represented in the Moderate to Severe MCI group (3.57%) compared to the Normal to Mild MCI group (22.84%). Employment status also differed significantly (p = 0.01). A smaller proportion of individuals in the Moderate to Severe MCI group were employed (25%) compared to the Normal to Mild MCI group (52.47%). Similarly, annual household income was significantly lower in the Moderate to Severe MCI group, with 89.29% reporting an income below $ 29,999 compared to 61.88% in the Normal to Mild MCI group (p = 0.02). Participants with Moderate to Severe MCI had a longer mean duration of residency in the U.S. (27.57 years, SD = 10.64) compared to those with Normal to Mild MCI (21.55 years, SD = 13.33), a statistically significant difference (p = 0.02). All other participant characteristics can be found in Table 1 . Table 1 Participant Characteristics by Cognitive Impairment Cognitive Impairment Normal to Mild MCI (n = 164) Moderate to Severe MCI (n = 30) n % n % p-value Sex* 0.57 Male 49 30.25 7 25 Female 113 69.75 21 75 Age 0.26 Less than 29 years 8 4.88 2 6.67 30 to 39 years 30 18.29 2 6.67 40 to 49 years 38 23.17 4 13.33 50 to 59 years 48 29.27 11 36.67 60 years older 40 24.39 11 36.67 Educational Attainment < 0.001 Grades 1–6 21 12.96 12 42.86 Grades 7–8 29 17.90 8 28.57 Grades 9–12 42 25.93 5 17.86 Some college 33 20.37 2 7.14 College degree or higher 37 22.84 1 3.57 Employment Status 0.01 Employed 85 52.47 7 25 Unemployed 77 47.53 21 75.00 Annual Household Income 0.02 Less than $ 29,999 99 61.88 25 89.29 $ 30,000 to $ 59,999 51 31.88 3 10.71 More than $ 60,000 10 6.25 - - Years in the U.S. ( M , SD ) 21.55 13.33 27.57 10.64 0.02 Smoking Status 0.09 Non-smokers 110 72.85 23 88.46 Smokers 41 27.15 3 11.54 Body Mass Index 0.39 Healthy weight (18.5 to 24.9) 19 11.59 3 10.00 Overweight (25 to 29.9) 71 43.29 17 56.67 Obesity (30 or greater) 74 45.12 10 33.33 MASLD Status 0.66 No MASLD 100 60.98 17 56.67 MASLD 64 39.02 13 43.33 High Blood Pressure 0.23 Normal 89 54.27 12 40.00 Elevated blood pressure 24 14.63 3 10.00 Stage 1 hypertension 37 22.56 10 33.33 Stage 2 hypertension 14 8.54 5 16.67 Note: Four participants refused to report their sex Table 1 . Participant Characteristics by Cognitive Impairment Cognitive Impairment Normal to Mild MCI (n = 164) Moderate to Severe MCI (n = 30) n % n % p-value Diabetes 0.48 Normal 69 42.07 10 33.33 Pre-diabetes 70 42.68 13 43.33 Diabetes 25 15.24 7 23.33 Depressive Symptoms 0.09 Non-clinical depressive symptoms 118 71.95 26 86.67 Clinical depressive symptoms 46 28.05 4 13.33 Perceived Stress 0.50 Low stress levels (≤ 13) 23 14.56 5 18.52 Moderate stress levels (14–26) 121 76.58 18 66.67 Elevated stress levels (≥ 27) 14 8.86 4 14.81 Unadjusted and Adjusted General Linear Models Unadjusted bivariate general linear models (Table 2 ) indicated that blood pressure, depressive symptoms, and educational attainment were significantly associated with cognitive function as measured by MoCA-S. Compared to participants with normal blood pressure levels, those with stage 1 hypertension exhibited lower MoCA-S scores (β=-1.80, 95% CI=-3.14, -0.46). Conversely, participants at risk for clinical depression (CES-D ≥ 16) demonstrated higher MoCA-S scores than those without risk (β = 1.36, 95% CI = 0.11, 2.62). Additionally, participants with educational levels between 7th and 8th grade (β = 1.82, 95% CI = 0.11, 3.53), 9th and 12th grade (β = 2.88, 95% CI = 1.26, 4.50), some college education (β = 2.25, 95% CI = 0.52, 3.97), and those with a college degree or higher (β = 5.00, 95% CI = 3.31, 6.70) achieved higher MoCA-S scores compared to those with less than a 6th -grade education. There were no statistically significant differences in MoCA-S scores regarding BMI, MASLD status, type 2 diabetes status, perceived stress, sex, age, and smoking status ( p > 0.05). The adjusted general linear model (Table 2 ) indicated that participants with a college degree or higher had higher MoCA-S scores than those with less than a 6th -grade level education (β = 3.67, 95% CI = 1.61, 5.72). No statistically significant differences in MoCA-S scores were observed for age, sex, years in the U.S., BMI, MASLD status, blood pressure, diabetes status, depressive symptoms, perceived stress, and smoking status ( p > 0.05). Table 2 Unadjusted and Adjusted Generalized Linear Models (GLMs) Unadjusted GLMs Adjusted GLMs n β 95% CI p-value β 95% CI p-value Sex Male 57 ref. --- --- ref. --- --- Female 134 0.23 -0.99–1.46 0.71 0.03 -1.44–1.50 0.97 Age Less than 29 years 10 ref. --- --- ref. --- --- 30 to 39 years 32 2.21 -0.48–4.90 0.11 -0.45 -4.19–3.28 0.81 40 to 49 years 42 1.68 -0.93–4.31 0.21 0.18 -3.56–3.91 0.93 50 to 59 years 59 -0.73 -3.27–1.82 0.57 -1.47 -5.26–2.32 0.45 60 years older 51 -0.08 -2.65–2.49 0.95 -1.04 -4.95–2.88 0.60 Educational Attainment Grades 1–6 33 ref. --- --- ref. --- --- Grades 7–8 37 1.82 0.11–3.53 0.04 1.23 -0.77–3.22 0.23 Grades 9–12 47 2.88 1.26–4.50 < 0.01 1.84 -0.08–3.73 0.06 Some college 35 2.25 0.52–3.97 0.01 1.20 -0.88–3.28 0.26 College degree or higher 38 5.00 3.31–6.70 < 0.001 3.67 1.61–5.72 < 0.01 Years in the US -0.02 -0.08–0.04 0.50 Smoking Status Non-smokers 133 ref. --- --- ref. --- --- Smokers 44 0.42 -0.92–1.76 0.53 -0.24 -1.68–1.20 0.74 Body Mass Index Healthy weight (18.5 to 24.9) 22 ref. --- --- ref. --- --- Overweight (25 to 29.9) 88 -0.64 -2.48–1.21 0.50 0.70 -1.32–2.71 0.50 Obesity (30 or greater) 84 -0.18 -2.03–1.67 0.85 1.58 -0.55–3.71 0.14 MASLD Status No MASLD 117 ref. --- --- ref. --- --- MASLD 77 0.57 -1.76–0.50 0.27 -0.79 -2.19–0.62 0.27 Blood Pressure Normal 101 ref. --- --- ref. --- --- Elevated blood pressure 27 -0.39 -2.04–1.25 0.63 0.22 -1.62–2.05 0.82 Stage 1 hypertension 47 -1.80 -3.14 – -0.46 0.01 -0.98 -2.57–0.61 0.23 Stage 2 hypertension 19 -1.72 -3.62–0.18 0.08 -0.42 -2.54–1.70 0.70 Diabetes Status Normal 79 ref. --- --- ref. --- --- Pre-diabetes 83 -0.47 -1.68–0.73 0.44 -0.59 -2.47–1.29 0.54 Type 2 Diabetes 32 -1.58 -3.19–0.03 0.05 -0.48 -1.81–0.86 0.48 Depressive Symptoms Non-clinical depressive symptoms 144 ref. --- --- ref. --- --- Clinical depressive symptoms 50 1.36 0.11–2.62 0.03 0.91 -0.49–2.31 0.20 Perceived Stress Low stress levels (≤ 13) 28 ref. --- --- ref. --- --- Moderate stress levels (14–26) 139 1.39 -0.21–2.99 0.08 0.65 -1.09–2.40 0.46 Elevated stress levels (≥ 27) 18 0.78 -1.55–3.11 0.51 -0.02 -2.60–2.56 0.99 Discussion This study aimed to characterize the prevalence and risk factors associated with MCI among Mexican-origin adults in Southern Arizona. In a study sample of 194 Mexican-origin participants, moderate to severe cognitive impairment was observed in 15.46% of participants. Further, a positive association between educational attainment and cognitive function was found. Despite some early effects, none of the cardiometabolic and mental health risk factors remained significant after adjusting for covariates. These findings contribute to the growing literature on cognitive health disparities, specifically for Mexican-origin populations. The results also underscore the importance of improving efforts for community-based screenings for Mexican-origin adults to reduce the burden of MCI and AD in the U.S., particularly as rates are expected to rise. Consistent with prior research, educational attainment emerged as a critical protective factor for cognitive function in this study. Higher education levels were associated with better cognitive outcomes, likely due to the development of cognitive reserve, which enables individuals to withstand age-related brain changes and resist MCI [ 36 – 38 ]. Education also improves health literacy, access to healthcare, and management of chronic diseases such as CVD and T2D, further reducing MCI risk [ 36 ]. However, systemic barriers to educational attainment in Mexican-origin communities, such as limited access to quality schools, lower college attendance rates, and socioeconomic inequities, may exacerbate cognitive health disparities [ 37 ]. Beyond formal schooling, participation in cognitively stimulating activities throughout adulthood can reinforce cognitive resilience, highlighting the importance of educational interventions such as health workshops and skill-building programs [ 38 ]. These findings suggest that promoting educational opportunities beyond formal education may mitigate cognitive health disparities in Mexican-origin adults. In addition, cardiometabolic and mental health risk factors were not significantly associated with MCI in the Mexican-origin population. This finding diverges from prior studies in broader Hispanic and NHW populations where these conditions are well-documented contributors to cognitive impairment [ 7 , 10 , 14 , 39 , 40 ]. The disparate set of results could be attributed to the fact that our community-based sample is relatively younger (mean age: 51.64 years) compared to the previous studies in this area of research and, therefore, may have fewer comorbid conditions associated with aging [ 41 ]. However, it is noteworthy that a significant proportion of participants (63.34%) with moderate to severe MCI in the study were under the age of 60; this has important clinical and public health implications. Particularly as it has been shown that Mexican-origin adults, like other Hispanic populations, tend to experience cognitive decline at younger ages compared to NHWs [ 4 , 5 , 8 ]. Thus, additional efforts are needed to identify and address unique drivers of early onset MCI among this high-risk population. These results underscore the need to shift cognitive screening efforts for Mexican-origin adults to younger age groups to slow disease progression and reduce the overall burden of MCI [ 42 ]. Strengths and Limitations Though this study identified significant predictors of MCI among Mexican-origin adults, several limitations should be noted when interpreting the results. The regional focus on Southern Arizona may restrict the generalizability of the findings to other Mexican-origin populations in the U.S., particularly those in urban areas or regions with differing sociocultural and healthcare contexts. However, our study used a community-based sample which ensures the inclusion of a diverse and representative sample of study participants, capturing a broader spectrum of cognitive health compared to clinic-based studies, which often focus on more advanced cases of MCI and dementia [ 43 , 44 ]. In addition, the study used the MoCA-S, a validated tool designed to detect subtle cognitive impairments in Spanish-speaking adults. By addressing language barriers and cultural nuances, the MoCA-S provides a more accurate assessment of cognitive function in Mexican-origin adults, reducing biases associated with traditional screening tools designed for English-speaking populations [ 22 , 42 ]. While, the small sample size, particularly within the moderate to severe MCI group, may have reduced the statistical power to detect associations with certain risk factors, such as cardiometabolic conditions. Examining cardiometabolic and psychosocial risk factors offers a holistic perspective, highlighting the complex interplay of sociodemographic, health-related, and mental health variables in shaping cognitive outcomes. In addition, including sociodemographic data, such as educational attainment and duration of U.S. residency, provides valuable insights into the role of social determinants of health, an area often underexplored in cognitive health research. Nevertheless, future research will be essential to deepen the understanding of MCI in Mexican-origin adults and to inform effective and equitable cognitive health interventions. Conclusion Expanding the use of the MoCA-S in community-based settings could facilitate earlier detection of cognitive decline, enabling timely interventions that improve long-term outcomes for Spanish-speaking individuals. By addressing key factors such as improving educational strategies while leveraging culturally sensitive screening tools, public health efforts can mitigate the burden of MCI in this high-risk population. Collaborative strategies among researchers, healthcare providers, and community organizations are necessary to advance cognitive health equity for Mexican-origin adults. Declarations Main Text Word Count 2,967 Total Number of Tables 2 Funding statement This work was supported by the American Cancer Society Cancer Health Equity Research Centers Grant, USA, (#MSI-21–167-01) Badger, T. (PI) / Garcia, D. Project PI. Author Contribution SL: Writing – review & editing, Writing – original draft, Methodology, Investigation, Conceptualization. AM: Writing – review & editing, Writing – original draft, Methodology, Investigation, Conceptualization, Formal Analysis. EOM: Writing – review & editing, Writing – original draft, Data curation. EV: Writing – review & editing, Writing – original draft, Data curation. MH: Writing – review & editing, Writing – original draft. DG: Writing – review & editing, Writing – original draft, Methodology, Investigation, Conceptualization, Funding acquisition. Acknowledgement We acknowledge all study participants, the Nosotros staff, and the University of Arizona Collaboratory for Metabolic Disease Prevention and Treatment. Data Availability 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. References Kasper S, Bancher C, Eckert A, Forstl H, Frolich L, Hort J, Korczyn AD, Kressig RW, Levin O, Palomo MSM. Management of mild cognitive impairment (MCI): The need for national and international guidelines. World J Biol Psychiatry. 2020;21(8):579–94. https://doi.org/10.1080/15622975.2019.1696473 . Cary Funk MHL. 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Arce Renteria M, Manly JJ, Vonk JMJ, Mejia Arango S, Michaels Obregon A, Samper-Ternent R, Wong R, Barral S, Tosto G. Midlife Vascular Factors and Prevalence of Mild Cognitive Impairment in Late-Life in Mexico. J Int Neuropsychol Soc. 2022;28(4):351–61. https://doi.org/10.1017/S1355617721000539 . Wong CG, Miller JB, Zhang F, Rissman RA, Raman R, Hall JR, Petersen M, Yaffe K, Kind AJ, O'Bryant SE, Team H-HS. Evaluation of Neighborhood-Level Disadvantage and Cognition in Mexican American and Non-Hispanic White Adults 50 Years and Older in the US. JAMA Netw Open. 2023;6(8):e2325325. https://doi.org/10.1001/jamanetworkopen.2023.25325 . Cersonsky TEK, Mechery S, Carper MM, Thompson L, Lee A, Alber J, Sarkar IN, Brick LAD. Using the Montreal cognitive assessment to identify individuals with subtle cognitive decline. Neuropsychology. 2022;36(5):373–83. https://doi.org/10.1037/neu0000820 . Gonzalez HM, Tarraf W, Fornage M, Gonzalez KA, Chai A, Youngblood M, Abreu MLA, Zeng D, Thomas S, Talavera GA, Gallo LC, Kaplan R, Daviglus ML, Schneiderman N. A research framework for cognitive aging and Alzheimer's disease among diverse US Latinos: Design and implementation of the Hispanic Community Health Study/Study of Latinos-Investigation of Neurocognitive Aging (SOL-INCA). Alzheimers Dement. 2019;15(12):1624–32. https://doi.org/10.1016/j.jalz.2019.08.192 . Mattke S, Jun H, Chen E, Liu Y, Becker A, Wallick C. Expected and diagnosed rates of mild cognitive impairment and dementia in the U.S. Medicare population: observational analysis. Alzheimers Res Ther. 2023;15(1):128. https://doi.org/10.1186/s13195-023-01272-z . Aguilar-Navarro SG, Mimenza-Alvarado AJ, Palacios-García AA, Samudio-Cruz A, Gutiérrez-Gutiérrez LA, Ávila-Funes JA. Validity and Reliability of the Spanish Version of the Montreal Cognitive Assessment (MoCA) for the Detection of Cognitive Impairment in Mexico. Rev Colomb Psiquiatr (Engl Ed). 2018;47(4):237–43. https://doi.org/10.1016/j.rcp.2017.05.003 . Lohman TG, Roche AF, Martorell R. Anthropometric standardization reference manual. Human kinetics books; 1988. (CDC). C.f.D.C.a.P., Blood Pressure-Oscillometric Measurement Procedures Manual , N.C.f.H.S. (NCHS). Editor. 2021. Whelton PK, Carey RM, Aronow WS, Casey DE Jr., Collins KJ, Dennison Himmelfarb C, DePalma SM, Gidding S, Jamerson KA, Jones DW, MacLaughlin EJ, Muntner P, Ovbiagele B, Smith SC Jr., Spencer CC, Stafford RS, Taler SJ, Thomas RJ, Williams KA, Wright SJT Jr., ACC/AHA/AAPA/ABC/. ACPM/AGS/APhA/ASH/ASPC/NMA/PCNA Guideline for the Prevention, Detection, Evaluation, and Management of High Blood Pressure in Adults: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Hypertension, 71(6), e13-e115. https://doi.org/10.1161/HYP.0000000000000065 Caussy C, Alquiraish MH, Nguyen P, Hernandez C, Cepin S, Fortney LE, Ajmera V, Bettencourt R, Collier S, Hooker J. Optimal threshold of controlled attenuation parameter with MRI-PDFF as the gold standard for the detection of hepatic steatosis. Hepatology. 2018;67(4):1348–59. Centers for Disease Control and Prevention. Liver Ultrasound Transient Elastography Procedures Manual N.H.a.N.E.S. (NHANES), Editor. 2018. (2025). 2. Diagnosis and Classification of Diabetes: Standards of Care in Diabetes—2025. Diabetes Care, 48(Supplement_1), S27–49. Orme JG, Reis J, Herz EJ. Factorial and discriminant validity of the Center for Epidemiological Studies Depression (CES-D) scale. J Clin Psychol. 1986;42(1):28–33. https://doi.org/10.1002/1097-4679(198601)42:1 . Baik SH, Fox RS, Mills SD, Roesch SC, Sadler GR, Klonoff EA, Malcarne VL. Reliability and validity of the Perceived Stress Scale-10 in Hispanic Americans with English or Spanish language preference. J Health Psychol. 2019;24(5):628–39. https://doi.org/10.1177/1359105316684938 . SAS Institute Inc. SAS/STAT 14.1 User’s Guide. Cary, NC: SAS Institute Inc; 2015. Mendoza L, Garcia P, Duara R, Rosselli M, Loewenstein D, Greig-Custo MT, Barker W, Dahlin P, Rodriguez MJ. The effect of acculturation on cognitive performance among older Hispanics in the United States. Appl Neuropsychol Adult. 2022;29(2):163–71. https://doi.org/10.1080/23279095.2020.1725888 . Aguayo-Mazzucato C, Diaque P, Hernandez S, Rosas S, Kostic A, Caballero AE. Understanding the growing epidemic of type 2 diabetes in the Hispanic population living in the United States. Diabetes Metab Res Rev. 2019;35(2):e3097. https://doi.org/10.1002/dmrr.3097 . Farina MP, Hayward MD, Kim JK, Crimmins EM. Racial and Educational Disparities in Dementia and Dementia-Free Life Expectancy. J Gerontol B Psychol Sci Soc Sci. 2020;75(7):e105–12. https://doi.org/10.1093/geronb/gbz046 . Lovden M, Fratiglioni L, Glymour MM, Lindenberger U, Tucker-Drob EM. Education and Cognitive Functioning Across the Life Span. Psychol Sci Public Interest. 2020;21(1):6–41. https://doi.org/10.1177/1529100620920576 . Campbell NL, Unverzagt F, LaMantia MA, Khan BA, Boustani MA. Risk factors for the progression of mild cognitive impairment to dementia. Clin Geriatr Med. 2013;29(4):873–93. https://doi.org/10.1016/j.cger.2013.07.009 . Stickel A, McKinnon A, Ruiz J, Grilli MD, Ryan L, Alzheimer I, 's Disease Neuroimaging. The impact of cardiovascular risk factors on cognition in Hispanics and non-Hispanic whites. Learn Mem. 2019;26(7):235–44. https://doi.org/10.1101/lm.048470.118 . Márquez F, Tarraf W, Stickel AM, González KA, Testai FD, Cai J, Gallo LC, Talavera GA, Daviglus ML, Wassertheil-Smoller S, DeCarli C, Schneiderman N, González HM. Hypertension, Cognitive Decline, and Mild Cognitive Impairment Among Diverse Hispanics/Latinos: Study of Latinos-Investigation of Neurocognitive Aging Results (SOL-INCA). J Alzheimers Dis. 2024;97(3):1449–61. https://doi.org/10.3233/jad-230424 . Mattke S, Batie D, Chodosh J, Felten K, Flaherty E, Fowler NR, Kobylarz FA, O'Brien K, Paulsen R, Pohnert A, Possin KL, Sadak T, Ty D, Walsh A, Zissimopoulos JM. Expanding the use of brief cognitive assessments to detect suspected early-stage cognitive impairment in primary care. Alzheimers Dement. 2023;19(9):4252–9. https://doi.org/10.1002/alz.13051 . Farias ST, Mungas D, Reed BR, Harvey D, DeCarli C. Progression of mild cognitive impairment to dementia in clinic- vs community-based cohorts. Arch Neurol. 2009;66(9):1151–7. https://doi.org/10.1001/archneurol.2009.106 . Garg M, Hejazi S, Fu S, Vassilaki M, Petersen RC, J. St. Sauver, and, Sohn S. (2024). Characterizing the progression from mild cognitive impairment to dementia: a network analysis of longitudinal clinical visits. BMC Medical Informatics and Decision Making, 24(1), 305. https://doi.org/10.1186/s12911-024-02711-z Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8414548","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":565515219,"identity":"e25b4929-c672-4791-96c0-4b3d7c1c0f01","order_by":0,"name":"Shannon Lindemer","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABEklEQVRIiWNgGAWjYDACCQglw8bAYABiyDEwMDZA5RLwauGBaTEmXgsDVEtiA0IOuxb52c3PHhdU3OHhk27e+OhGxb30/tmHmz983GHHwM+eY4BNi8GdY+bGM84842GTOVZsnHOmOHfGucQGw5lnkhkke95g1yKRYCbN23aYh00ix0w6ty0ht+EMY0Mybxszg8EN7LbIz0j/BtNi/jv3X0K6PFDLYd62egZ7HFoYbuQgbGHObUhIMDjD2NgMFAE6AIdfbuSUSfOcAWlJK5bOOZZguPEMYzPjzLbjPBJnnhXgcNg2aZ6Kw3LyM5I3fs6pSZCXO8P++MPHtmo5/vbkDVgdhhPwkKZ8FIyCUTAKRgEyAACeO1xv4eN0yQAAAABJRU5ErkJggg==","orcid":"","institution":"University of Arizona","correspondingAuthor":true,"prefix":"","firstName":"Shannon","middleName":"","lastName":"Lindemer","suffix":""},{"id":565515221,"identity":"939bad02-14e7-4cd7-9237-501570f4c59d","order_by":1,"name":"Adriana Maldonado","email":"","orcid":"","institution":"University of Arizona","correspondingAuthor":false,"prefix":"","firstName":"Adriana","middleName":"","lastName":"Maldonado","suffix":""},{"id":565515224,"identity":"f8e3e5c1-0935-48b8-bf00-ca775d8d9b6c","order_by":2,"name":"Estefania Ochoa-Mora","email":"","orcid":"","institution":"University of Arizona","correspondingAuthor":false,"prefix":"","firstName":"Estefania","middleName":"","lastName":"Ochoa-Mora","suffix":""},{"id":565515225,"identity":"c646db4c-3fcb-40df-8772-ff7d9e45bbe8","order_by":3,"name":"Edgar Villavicencio","email":"","orcid":"","institution":"University of Arizona","correspondingAuthor":false,"prefix":"","firstName":"Edgar","middleName":"","lastName":"Villavicencio","suffix":""},{"id":565515228,"identity":"ff78b091-5e9b-42f5-bedc-d52ef5e0e638","order_by":4,"name":"Matthew Huentelman","email":"","orcid":"","institution":"Translational Genomics Research Institute","correspondingAuthor":false,"prefix":"","firstName":"Matthew","middleName":"","lastName":"Huentelman","suffix":""},{"id":565515229,"identity":"d2a78c0e-f8ab-4983-a31c-83bd9e0fda51","order_by":5,"name":"David Garcia","email":"","orcid":"","institution":"University of Arizona","correspondingAuthor":false,"prefix":"","firstName":"David","middleName":"","lastName":"Garcia","suffix":""}],"badges":[],"createdAt":"2025-12-20 23:38:10","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8414548/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8414548/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":103789388,"identity":"d0f36b9e-0ca6-44c2-8ca5-24e4f462b42d","added_by":"auto","created_at":"2026-03-03 01:39:58","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1377792,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8414548/v1/2304d526-5820-4125-b461-c8efa1e9ed3e.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Mild Cognitive Impairment Prevalence and Associated Risk Factor Frequency Among Mexican-origin Adults in Southern Arizona","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMild Cognitive Impairment (MCI) is distinguished by a decrease in one or more cognitive domains[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. While previous work suggests the existence of a strong association between MCI risk factors (e.g., obesity, cardiovascular disease (CVD), and type 2 diabetes (T2D)) and the rate of progression of MCI; the majority of these findings are derived from non-Hispanic white (NHW) populations. This is a significant gap in the MCI literature, as nearly 18% of the United States (U.S.) population is Hispanic [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. By 2060, the number of people in this group aged 65 and older is expected to reach 20\u0026nbsp;million, with rates of MCI and Alzheimer's disease (AD) increasing six-fold [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. This is particularly relevant for Mexican-origin adults in the U.S., who comprise approximately 60% of the Hispanic population and experience a disproportionate burden of modifiable risk factors for MCI, such as CVD and T2D [\u003cspan additionalcitationids=\"CR5 CR6\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. In addition, studies indicate that Mexican-origin adults are often diagnosed with MCI, dementia, and AD at more advanced stages and younger ages compared to other Hispanic subgroups and NHWs [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Therefore, efforts to characterize risk factors associated with MCI among Mexican-origin adults are necessary to reduce the burden of this disease for this high-risk community.\u003c/p\u003e \u003cp\u003eIn Hispanic populations, prevalent modifiable risk factors increase the likelihood of developing MCI and progressing to dementia through cardiometabolic, vascular, and psychological pathways [\u003cspan additionalcitationids=\"CR10 CR11\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. These conditions can interact and exacerbate each other, worsening cognitive health outcomes. For instance, obesity heightens the risk of developing T2D, CVD (e.g., hypertension), and metabolic dysfunction-associated steatotic liver disease (MASLD), which increases MCI risk through vascular dysfunction and metabolic abnormalities [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Moreover, poor glycemic control links T2D to MCI via vascular complications in the brain and accelerates cognitive decline by up to seven years among Hispanic adults [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Depression exacerbates MCI risk, particularly for individuals who experience chronic stress [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Lastly, additional risk factors, including age, sex, and educational attainment, often linked to socioeconomic disparities, elevate the risk of MCI for Mexican-origin adults [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMexican-origin adults\u0026rsquo; risk for MCI is further compounded by sociocultural factors such as limited access to healthcare, perceptions of MCI risk, and the ability to receive culturally congruent care [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. In fact, the early screening and detection of cognitive decline requires comprehensive neuropsychological testing, the most reliable clinical method; however, brief medical appointments and long waits for testing pose significant challenges [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. There are also many practical challenges to conducting MCI testing among English and Spanish-speaking Hispanics, including the use of appropriate cognitive assessment tools with normative cognitive data [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Detecting MCI, particularly in preclinical stages, is crucial to mitigate the burden of this disease among Mexican-origin adults and to reduce progression to AD [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe current study aimed to characterize the prevalence of MCI using the Spanish version of the Montreal Cognitive Assessment (MoCA-S) among Mexican-origin adults in Southern Arizona and to identify risk factors associated with MCI in this population. Specifically, we evaluated the impact of sociodemographic characteristics (e.g., educational attainment), cardiometabolic (e.g., hypertension), and mental health (e.g., depression) risk factors on cognitive function among this vulnerable population.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design, Sample, and Data Collection Procedures\u003c/h2\u003e \u003cp\u003eA community-based cross-sectional sample of 194 Mexican-origin adults residing in the Southern Arizona U.S./Mexico border region was recruited. Eligible participants self-identified as foreign-born Mexican-origin adults who were at least 18 years of age, able to provide informed consent, and proficient in speaking, reading, and writing in either English or Spanish. Participants were recruited through three primary strategies: face-to-face interactions during community outreach events (e.g., local swap meet/flea market and Mexican Consulate), distribution of study-related flyers, and word of mouth.\u003c/p\u003e \u003cp\u003eData collection occurred between May 2023 and February 2024. Individuals expressing interest in the study completed a screening questionnaire at recruitment events to determine eligibility. Those who met the eligibility criteria were invited to the University of Arizona Collaboratory for Metabolic Disease Prevention and Treatment to complete a 90-minute in-person visit which consisted of written informed consent, cognitive assessment, anthropometric measures, blood pressure, cardiometabolic blood values, FibroScan\u0026reg;, and self-reported questionnaires. Study visits and self-reported questionnaires were completed in either Spanish or English, depending on the participants\u0026rsquo; preferred language. After completing all data collection procedures, participants were compensated \u003cspan\u003e$\u003c/span\u003e50 for their time. Ethical approval for all study materials and research protocol was obtained from the University of Arizona\u0026rsquo;s Institutional Review Board under protocol STUDY00001145.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eMeasures\u003c/h3\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eMontreal Cognitive Assessment in Spanish\u003c/h2\u003e \u003cp\u003eCognitive function was evaluated using the validated Montreal Cognitive Assessment in Spanish v8.1 (MoCA-S), a valid and reliable instrument for MCI and dementia screening in Mexican-origin populations [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. The MoCA-S was administered by research staff who were formally trained in its administration by a professional certified psychometrist, ensuring standardized administration. Scores range from 0 to 30, with higher scores indicating better cognitive performance. Participants with less than 12 years of education received an additional point to adjust for educational disparities. We followed established MoCA interpretation guidelines, categorizing scores as normal (26\u0026ndash;30), mild (18\u0026ndash;25), moderate (10\u0026ndash;17), and severe (\u0026lt;\u0026thinsp;10), consistent with validation studies in Spanish-speaking populations [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Due to small cell sizes, MoCA-S scores were dichotomized as \u0026ldquo;normal to mild MCI\u0026rdquo; and \u0026ldquo;moderate to severe MCI.\u0026rdquo;\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eCardiometabolic Risk Factors\u003c/h3\u003e\n\u003cp\u003e \u003cem\u003eBody Mass Index (BMI).\u003c/em\u003e Using a wall-mounted stadiometer (ShorrBoard\u0026reg;), participants\u0026rsquo; height was measured without shoes, twice to the nearest 0.1 cm. Without shoes and in participants\u0026rsquo; street clothes, participants\u0026rsquo; weight was measured twice on a calibrated digital scale (Seca 8760) to the nearest 0.1 kg.[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] BMI was computed by dividing the average body weight in kilograms by squared average height in meters (kg/m\u003csup\u003e2\u003c/sup\u003e) and classified into standard categories: healthy weight (18.5 to 24.9 kg/m\u003csup\u003e2\u003c/sup\u003e), overweight (25 to 29.9 kg/m\u003csup\u003e2\u003c/sup\u003e), and obesity (\u0026ge;\u0026thinsp;30 kg/m\u003csup\u003e2\u003c/sup\u003e).\u003c/p\u003e \u003cp\u003e\u003cem\u003eBlood Pressure.\u003c/em\u003e A digital blood pressure monitor (Omron HEM-907XL) was used to measure systolic (SBP) and diastolic blood pressure (DBP).[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] Measurements followed the National Health and Nutrition Examination Survey protocol: two seated blood pressure readings were obtained after a rest period of at least five minutes, with a third reading taken if there was notable variability between the first two. The average of the valid readings was used in all analyses to ensure accuracy and reliability [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Participants\u0026rsquo; blood pressure readings were classified as normal (SBP\u0026thinsp;\u0026lt;\u0026thinsp;120 mmHg and DBP\u0026thinsp;\u0026lt;\u0026thinsp;80mmHg), elevated (120\u0026ndash;129 mmHg and DBP\u0026thinsp;\u0026lt;\u0026thinsp;80mmHg), stage 1 hypertension (130\u0026ndash;139 mmHg or DBP 80\u0026ndash;89 mmHg), and stage 2 hypertension (\u0026ge;\u0026thinsp;140 mmHg or DBP\u0026thinsp;\u0026ge;\u0026thinsp;90 mmHg) [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. These categories were selected in accordance with the 2017 American College of Cardiology/American Heart Association (ACC/AHA) clinical practice guidelines for the prevention, detection, evaluation, and management of high blood pressure in adults, to ensure consistency with established standards and facilitate comparability with other studies [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cem\u003eMetabolic Dysfunction-Associated Steatotic Liver Disease Status.\u003c/em\u003e MASLD was identified via vibration-controlled transient elastography (FibroScan\u0026reg; 430 MINI+). A continuous attenuation parameter (CAP) score of \u0026ge;\u0026thinsp;288 dB/m indicated MASLD status [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Scans were considered complete and valid if participants fasted for at least three hours, and a total of 10 liver stiffness measurement (LSM) measures were obtained with an interquartile range (IQR)/median value of less or equal than 30% [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cem\u003eType 2 Diabetes Status.\u003c/em\u003e Hemoglobin A1C (HbA1C) levels were determined via fasting blood samples analyzed by a commercial laboratory. Participants\u0026rsquo; HbA1C levels were classified as normal (\u0026lt;\u0026thinsp;5.7%), prediabetes (5.7% \u0026ndash; 6.4%), and diabetes (\u0026gt;\u0026thinsp;6.5%) [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eMental Health Risk Factors\u003c/h3\u003e\n\u003cp\u003e \u003cem\u003eDepressive Symptoms.\u003c/em\u003e The Center for Epidemiological Studies-Depression (CES-D) scale, a 20-item self-report, was used to assess depressive symptoms experienced in the past week [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Scores range from 0 to 60, with a cutoff of \u0026ge;\u0026thinsp;16 indicating risk for clinical depression.\u003c/p\u003e \u003cp\u003e \u003cem\u003ePerceived Stress.\u003c/em\u003e Levels of perceived stress were measured using the Perceived Stress Scale (PSS-10), a valid and reliable measure in Hispanic populations [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. The four positively worded items (Items 4, 5, 7, 8) were reversed scored, and a total score was computed by adding all 10 items ranging from 0 to 40. Perceived stress levels were categorized as low stress (\u0026le;\u0026thinsp;13), moderate stress (14\u0026ndash;26), and elevated stress (\u0026ge;\u0026thinsp;27).\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eSociodemographic Characteristics and Health-related Behaviors\u003c/h2\u003e \u003cp\u003eDescriptive variables, including age, sex, educational attainment, time of residence in the U.S., employment status, and smoking status, were included as covariates in the analyses of the current study.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStatistical Analyses\u003c/h3\u003e\n\u003cp\u003eA complete case data analysis was conducted using SAS software [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Summary statistics were used to describe the analytical sample stratified by cognitive function status. Generalized linear models using PROC GLM, were used to estimate unadjusted and adjusted mean differences in cognitive functioning scores (MoCA-S) for participants\u0026rsquo; cardiometabolic risk factors (i.e., BMI, blood pressure, MASLD, and T2D status), mental health risk factors (i.e., depressive symptoms and perceived stress), and sociodemographic characteristics and health variables (i.e., age, sex, educational attainment, and smoking status). As acculturation has been associated with cognitive performance among Hispanics[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e], the general linear models adjusted for years in the U.S., a proxy measure of acculturation. Two-sided p-values of \u0026lt;\u0026thinsp;0.05 were considered statistically significant.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eParticipant Characteristics\u003c/h2\u003e \u003cp\u003eOf the total sample, 15.5% (n\u0026thinsp;=\u0026thinsp;30) of participants were identified with moderate to severe MCI, which includes 8 participants between 18 and 49 years (26.7%), 11 participants between 59 and 59 years (36.7%) and 11 participants aged 60 years and over (36.7%). Educational attainment varied significantly between the groups (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Individuals in the Moderate to Severe MCI group were more likely to have completed only grades 1\u0026ndash;6 (42.86%) compared to 12.96% in the Normal to Mild MCI group. Conversely, participants with a college degree or higher were less represented in the Moderate to Severe MCI group (3.57%) compared to the Normal to Mild MCI group (22.84%). Employment status also differed significantly (p\u0026thinsp;=\u0026thinsp;0.01). A smaller proportion of individuals in the Moderate to Severe MCI group were employed (25%) compared to the Normal to Mild MCI group (52.47%). Similarly, annual household income was significantly lower in the Moderate to Severe MCI group, with 89.29% reporting an income below \u003cspan\u003e$\u003c/span\u003e29,999 compared to 61.88% in the Normal to Mild MCI group (p\u0026thinsp;=\u0026thinsp;0.02). Participants with Moderate to Severe MCI had a longer mean duration of residency in the U.S. (27.57 years, SD\u0026thinsp;=\u0026thinsp;10.64) compared to those with Normal to Mild MCI (21.55 years, SD\u0026thinsp;=\u0026thinsp;13.33), a statistically significant difference (p\u0026thinsp;=\u0026thinsp;0.02). All other participant characteristics can be found in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eParticipant Characteristics by Cognitive Impairment\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c7\" namest=\"c3\"\u003e \u003cp\u003eCognitive Impairment\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eNormal to Mild MCI\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;164)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eModerate to Severe MCI\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;30)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e113\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e69.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLess than 29 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30 to 39 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40 to 49 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e13.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50 to 59 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e36.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60 years older\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e36.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducational Attainment\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGrades 1\u0026ndash;6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e42.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGrades 7\u0026ndash;8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e28.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGrades 9\u0026ndash;12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e17.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSome college\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCollege degree or higher\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEmployment Status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEmployed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e52.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnemployed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e47.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e75.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAnnual Household Income\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLess than \u003cspan\u003e$\u003c/span\u003e29,999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e61.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e89.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cspan\u003e$\u003c/span\u003e30,000 to \u003cspan\u003e$\u003c/span\u003e59,999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e10.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMore than \u003cspan\u003e$\u003c/span\u003e60,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eYears in the U.S. (\u003c/b\u003e\u003cb\u003eM\u003c/b\u003e, \u003cb\u003eSD\u003c/b\u003e\u003cb\u003e)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e27.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e10.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSmoking Status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNon-smokers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e72.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e88.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSmokers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e11.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBody Mass Index\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHealthy weight (18.5 to 24.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e10.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOverweight (25 to 29.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e43.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e56.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eObesity (30 or greater)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e45.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e33.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMASLD Status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.66\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo MASLD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e60.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e56.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMASLD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e43.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHigh Blood Pressure\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e54.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e40.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eElevated blood pressure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e10.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStage 1 hypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e33.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStage 2 hypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e16.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003e\u003csup\u003eNote: Four participants refused to report their sex\u003c/sup\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Participant Characteristics by Cognitive Impairment\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c7\" namest=\"c3\"\u003e \u003cp\u003eCognitive Impairment\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eNormal to Mild MCI\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;164)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eModerate to Severe MCI\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;30)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDiabetes\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e33.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePre-diabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e43.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDiabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e23.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDepressive Symptoms\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNon-clinical depressive symptoms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e71.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e86.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eClinical depressive symptoms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e13.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePerceived Stress\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow stress levels (\u0026le;\u0026thinsp;13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e18.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModerate stress levels (14\u0026ndash;26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e121\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e76.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e66.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eElevated stress levels (\u0026ge;\u0026thinsp;27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e14.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eUnadjusted and Adjusted General Linear Models\u003c/h2\u003e \u003cp\u003eUnadjusted bivariate general linear models (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) indicated that blood pressure, depressive symptoms, and educational attainment were significantly associated with cognitive function as measured by MoCA-S. Compared to participants with normal blood pressure levels, those with stage 1 hypertension exhibited lower MoCA-S scores (β=-1.80, 95% CI=-3.14, -0.46). Conversely, participants at risk for clinical depression (CES-D\u0026thinsp;\u0026ge;\u0026thinsp;16) demonstrated higher MoCA-S scores than those without risk (β\u0026thinsp;=\u0026thinsp;1.36, 95% CI\u0026thinsp;=\u0026thinsp;0.11, 2.62). Additionally, participants with educational levels between 7th and 8th grade (β\u0026thinsp;=\u0026thinsp;1.82, 95% CI\u0026thinsp;=\u0026thinsp;0.11, 3.53), 9th and 12th grade (β\u0026thinsp;=\u0026thinsp;2.88, 95% CI\u0026thinsp;=\u0026thinsp;1.26, 4.50), some college education (β\u0026thinsp;=\u0026thinsp;2.25, 95% CI\u0026thinsp;=\u0026thinsp;0.52, 3.97), and those with a college degree or higher (β\u0026thinsp;=\u0026thinsp;5.00, 95% CI\u0026thinsp;=\u0026thinsp;3.31, 6.70) achieved higher MoCA-S scores compared to those with less than a 6th -grade education. There were no statistically significant differences in MoCA-S scores regarding BMI, MASLD status, type 2 diabetes status, perceived stress, sex, age, and smoking status (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003eThe adjusted general linear model (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) indicated that participants with a college degree or higher had higher MoCA-S scores than those with less than a 6th -grade level education (β\u0026thinsp;=\u0026thinsp;3.67, 95% CI\u0026thinsp;=\u0026thinsp;1.61, 5.72). No statistically significant differences in MoCA-S scores were observed for age, sex, years in the U.S., BMI, MASLD status, blood pressure, diabetes status, depressive symptoms, perceived stress, and smoking status (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eUnadjusted and Adjusted Generalized Linear Models (GLMs)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"12\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c8\" namest=\"c4\"\u003e \u003cp\u003eUnadjusted GLMs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c12\" namest=\"c10\"\u003e \u003cp\u003eAdjusted GLMs\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eβ\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eβ\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"12\" nameend=\"c12\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eref.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eref.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e-0.99\u0026ndash;1.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-1.44\u0026ndash;1.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"12\" nameend=\"c12\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLess than 29 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eref.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eref.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30 to 39 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e2.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e-0.48\u0026ndash;4.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-4.19\u0026ndash;3.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.81\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40 to 49 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e1.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e-0.93\u0026ndash;4.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-3.56\u0026ndash;3.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50 to 59 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e-0.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e-3.27\u0026ndash;1.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-1.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-5.26\u0026ndash;2.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60 years older\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e-0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e-2.65\u0026ndash;2.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-1.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-4.95\u0026ndash;2.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.60\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"12\" nameend=\"c12\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducational Attainment\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGrades 1\u0026ndash;6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eref.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eref.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGrades 7\u0026ndash;8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e1.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e0.11\u0026ndash;3.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-0.77\u0026ndash;3.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGrades 9\u0026ndash;12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e2.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e1.26\u0026ndash;4.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-0.08\u0026ndash;3.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSome college\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e2.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e0.52\u0026ndash;3.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-0.88\u0026ndash;3.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCollege degree or higher\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e5.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e3.31\u0026ndash;6.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e3.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1.61\u0026ndash;5.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eYears in the US\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c9\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-0.08\u0026ndash;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"12\" nameend=\"c12\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSmoking Status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNon-smokers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e133\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eref.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eref.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSmokers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e-0.92\u0026ndash;1.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-1.68\u0026ndash;1.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.74\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"12\" nameend=\"c12\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBody Mass Index\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHealthy weight (18.5 to 24.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eref.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eref.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOverweight (25 to 29.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e-0.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e-2.48\u0026ndash;1.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-1.32\u0026ndash;2.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eObesity (30 or greater)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e-0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e-2.03\u0026ndash;1.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-0.55\u0026ndash;3.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"12\" nameend=\"c12\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMASLD Status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo MASLD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e117\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eref.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eref.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMASLD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e-1.76\u0026ndash;0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-2.19\u0026ndash;0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.27\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"12\" nameend=\"c12\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBlood Pressure\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eref.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eref.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eElevated blood pressure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e-0.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e-2.04\u0026ndash;1.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-1.62\u0026ndash;2.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.82\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStage 1 hypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e-1.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e-3.14 \u0026ndash; -0.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-2.57\u0026ndash;0.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStage 2 hypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e-1.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e-3.62\u0026ndash;0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-2.54\u0026ndash;1.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.70\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"12\" nameend=\"c12\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDiabetes Status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eref.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eref.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePre-diabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e-0.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e-1.68\u0026ndash;0.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-2.47\u0026ndash;1.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.54\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eType 2 Diabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e-1.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e-3.19\u0026ndash;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-1.81\u0026ndash;0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"12\" nameend=\"c12\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDepressive Symptoms\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNon-clinical depressive symptoms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eref.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eref.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eClinical depressive symptoms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e1.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e0.11\u0026ndash;2.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-0.49\u0026ndash;2.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"12\" nameend=\"c12\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePerceived Stress\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow stress levels (\u0026le;\u0026thinsp;13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eref.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eref.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e---\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModerate stress levels (14\u0026ndash;26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e139\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e1.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e-0.21\u0026ndash;2.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-1.09\u0026ndash;2.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.46\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eElevated stress levels (\u0026ge;\u0026thinsp;27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e-1.55\u0026ndash;3.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-2.60\u0026ndash;2.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study aimed to characterize the prevalence and risk factors associated with MCI among Mexican-origin adults in Southern Arizona. In a study sample of 194 Mexican-origin participants, moderate to severe cognitive impairment was observed in 15.46% of participants. Further, a positive association between educational attainment and cognitive function was found. Despite some early effects, none of the cardiometabolic and mental health risk factors remained significant after adjusting for covariates. These findings contribute to the growing literature on cognitive health disparities, specifically for Mexican-origin populations. The results also underscore the importance of improving efforts for community-based screenings for Mexican-origin adults to reduce the burden of MCI and AD in the U.S., particularly as rates are expected to rise.\u003c/p\u003e \u003cp\u003eConsistent with prior research, educational attainment emerged as a critical protective factor for cognitive function in this study. Higher education levels were associated with better cognitive outcomes, likely due to the development of cognitive reserve, which enables individuals to withstand age-related brain changes and resist MCI [\u003cspan additionalcitationids=\"CR37\" citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Education also improves health literacy, access to healthcare, and management of chronic diseases such as CVD and T2D, further reducing MCI risk [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. However, systemic barriers to educational attainment in Mexican-origin communities, such as limited access to quality schools, lower college attendance rates, and socioeconomic inequities, may exacerbate cognitive health disparities [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Beyond formal schooling, participation in cognitively stimulating activities throughout adulthood can reinforce cognitive resilience, highlighting the importance of educational interventions such as health workshops and skill-building programs [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. These findings suggest that promoting educational opportunities beyond formal education may mitigate cognitive health disparities in Mexican-origin adults.\u003c/p\u003e \u003cp\u003eIn addition, cardiometabolic and mental health risk factors were not significantly associated with MCI in the Mexican-origin population. This finding diverges from prior studies in broader Hispanic and NHW populations where these conditions are well-documented contributors to cognitive impairment [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. The disparate set of results could be attributed to the fact that our community-based sample is relatively younger (mean age: 51.64 years) compared to the previous studies in this area of research and, therefore, may have fewer comorbid conditions associated with aging [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. However, it is noteworthy that a significant proportion of participants (63.34%) with moderate to severe MCI in the study were under the age of 60; this has important clinical and public health implications. Particularly as it has been shown that Mexican-origin adults, like other Hispanic populations, tend to experience cognitive decline at younger ages compared to NHWs [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Thus, additional efforts are needed to identify and address unique drivers of early onset MCI among this high-risk population. These results underscore the need to shift cognitive screening efforts for Mexican-origin adults to younger age groups to slow disease progression and reduce the overall burden of MCI [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e].\u003c/p\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eStrengths and Limitations\u003c/h2\u003e \u003cp\u003eThough this study identified significant predictors of MCI among Mexican-origin adults, several limitations should be noted when interpreting the results. The regional focus on Southern Arizona may restrict the generalizability of the findings to other Mexican-origin populations in the U.S., particularly those in urban areas or regions with differing sociocultural and healthcare contexts. However, our study used a community-based sample which ensures the inclusion of a diverse and representative sample of study participants, capturing a broader spectrum of cognitive health compared to clinic-based studies, which often focus on more advanced cases of MCI and dementia [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. In addition, the study used the MoCA-S, a validated tool designed to detect subtle cognitive impairments in Spanish-speaking adults. By addressing language barriers and cultural nuances, the MoCA-S provides a more accurate assessment of cognitive function in Mexican-origin adults, reducing biases associated with traditional screening tools designed for English-speaking populations [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. While, the small sample size, particularly within the moderate to severe MCI group, may have reduced the statistical power to detect associations with certain risk factors, such as cardiometabolic conditions. Examining cardiometabolic and psychosocial risk factors offers a holistic perspective, highlighting the complex interplay of sociodemographic, health-related, and mental health variables in shaping cognitive outcomes. In addition, including sociodemographic data, such as educational attainment and duration of U.S. residency, provides valuable insights into the role of social determinants of health, an area often underexplored in cognitive health research. Nevertheless, future research will be essential to deepen the understanding of MCI in Mexican-origin adults and to inform effective and equitable cognitive health interventions.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eExpanding the use of the MoCA-S in community-based settings could facilitate earlier detection of cognitive decline, enabling timely interventions that improve long-term outcomes for Spanish-speaking individuals. By addressing key factors such as improving educational strategies while leveraging culturally sensitive screening tools, public health efforts can mitigate the burden of MCI in this high-risk population. Collaborative strategies among researchers, healthcare providers, and community organizations are necessary to advance cognitive health equity for Mexican-origin adults.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eMain Text Word Count\u003c/h2\u003e \u003cp\u003e2,967\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eTotal Number of Tables\u003c/strong\u003e \u003cp\u003e2\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding statement\u003c/h2\u003e \u003cp\u003eThis work was supported by the American Cancer Society Cancer Health Equity Research Centers Grant, USA, (#MSI-21\u0026ndash;167-01) Badger, T. (PI) / Garcia, D. Project PI.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eSL: Writing \u0026ndash; review \u0026amp; editing, Writing \u0026ndash; original draft, Methodology, Investigation, Conceptualization. AM: Writing \u0026ndash; review \u0026amp; editing, Writing \u0026ndash; original draft, Methodology, Investigation, Conceptualization, Formal Analysis. EOM: Writing \u0026ndash; review \u0026amp; editing, Writing \u0026ndash; original draft, Data curation. EV: Writing \u0026ndash; review \u0026amp; editing, Writing \u0026ndash; original draft, Data curation. MH: Writing \u0026ndash; review \u0026amp; editing, Writing \u0026ndash; original draft. DG: Writing \u0026ndash; review \u0026amp; editing, Writing \u0026ndash; original draft, Methodology, Investigation, Conceptualization, Funding acquisition.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eWe acknowledge all study participants, the Nosotros staff, and the University of Arizona Collaboratory for Metabolic Disease Prevention and Treatment.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe 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.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eKasper S, Bancher C, Eckert A, Forstl H, Frolich L, Hort J, Korczyn AD, Kressig RW, Levin O, Palomo MSM. Management of mild cognitive impairment (MCI): The need for national and international guidelines. World J Biol Psychiatry. 2020;21(8):579\u0026ndash;94. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/15622975.2019.1696473\u003c/span\u003e\u003cspan address=\"10.1080/15622975.2019.1696473\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCary Funk MHL. Hispanic Americans\u0026rsquo; Trust in and Engagement with Science. Pew Research Center; 2022.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRajan KB, Weuve J, Barnes LL, McAninch EA, Wilson RS, Evans DA. Population estimate of people with clinical Alzheimer's disease and mild cognitive impairment in the United States (2020\u0026ndash;2060). 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Characterizing the progression from mild cognitive impairment to dementia: a network analysis of longitudinal clinical visits. BMC Medical Informatics and Decision Making, 24(1), 305. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s12911-024-02711-z\u003c/span\u003e\u003cspan address=\"10.1186/s12911-024-02711-z\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Alzheimer’s disease, cardiometabolic syndrome, mental health, Hispanic, mild cognitive impairment, Montreal Cognitive Assessment (MoCA)","lastPublishedDoi":"10.21203/rs.3.rs-8414548/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8414548/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eLimited research exists among Mexican-origin populations related to Mild Cognitive Impairment (MCI) and Alzheimer\u0026rsquo;s Disease risk factors in community-based settings.\u003c/p\u003e\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eThis study aims to characterize the prevalence of MCI using the Montreal Cognitive Assessment in Spanish (MoCA-S) among Mexican-origin adults in Southern Arizona while identifying risk factors associated with MCI in this population.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA community-based sample of 194 Mexican-origin adults (women\u0026thinsp;=\u0026thinsp;134; men\u0026thinsp;=\u0026thinsp;56; mean age\u0026thinsp;=\u0026thinsp;51.64\u0026thinsp;\u0026plusmn;\u0026thinsp;12.3 years) in Southern Arizona participated in the study. The MoCA-S was administered and interpreted based on established cutoffs for cognitive function. A generalized linear model was fitted to explore the predictors of MCI while adjusting for sociodemographic, cardiometabolic, and mental health characteristics.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe mean MoCA-S score was 21.6 \u0026plusmn; 3.9, with 30 participants (15.46%) identified with mild to severe cognitive impairment. The adjusted model indicated that participants with a college degree or greater had higher MoCA-S scores compared to those with less than a 6th -grade level education (β\u0026thinsp;=\u0026thinsp;3.67, 95% CI\u0026thinsp;=\u0026thinsp;1.61, 5.72). No significant differences in MoCA-S scores were observed for age, sex, years in the U. S., body mass index, metabolic dysfunction-associated steatotic liver disease status, blood pressure, diabetes status, perceived stress, and smoking status (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThis study highlights the unique cognitive health challenges and opportunities within Mexican-origin communities in Southern Arizona. Addressing key factors, such as improving educational strategies while leveraging culturally sensitive screening tools, can support public health efforts to mitigate the burden of MCI in this high-risk population.\u003c/p\u003e","manuscriptTitle":"Mild Cognitive Impairment Prevalence and Associated Risk Factor Frequency Among Mexican-origin Adults in Southern Arizona","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-08 18:36:15","doi":"10.21203/rs.3.rs-8414548/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"803e81fd-b8f8-4e53-85ef-be2d45e08678","owner":[],"postedDate":"January 8th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-03-03T01:39:33+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-08 18:36:15","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8414548","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8414548","identity":"rs-8414548","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}