Association between anemia and cognitive dysfunction in the hypertensive elderly: a cross-sectional study

Association between anemia and cognitive dysfunction in the hypertensive elderly: a cross-sectional study | 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 Association between anemia and cognitive dysfunction in the hypertensive elderly: a cross-sectional study Libo Luo, Jiamei He, Xiaoli Liu, Qingyu Xiao This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5470638/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 Cognitive dysfunction has become one of the most serious social health problems around the world. Anemia may increase the risk of cognitive dysfunction in elderly population. Hypertension may also deteriorate cognitive function. Few studies reported the association of anemia and cognitive dysfunction in hypertensive elderly. Methods Data were obtained from the 2011–2014 National Health and Nutrition Examination Survey (NHANES). Cognitive performance was evaluated by the Consortium to Establish a Registry for Alzheimer’s Disease (CERAD) Word Learning subtest, the Animal Fluency Test (AFT), and the Digit Symbol Substitution Test (DSST). Multivariate logistic regression analysis and subgroup analysis were conducted to assess the relationship between anemia and cognitive dysfunction. Results A total of 2005 elderly participants (aged ≥ 60 years) were included. Anemia was associated with the greater risk of low cognitive performance in hypertensive elderly (OR = 1.427, 95% CI: 1.065–1.911). Anemia was associated with lower performance in AFT (OR = 1.331, 95% CI: 1.008–1.758) and DSST (OR = 1.818, 95% CI: 1.335–2.475). In subgroups of age younger than 65 or older than 80 years, being a female, being non-Hispanic White, with poverty income ratio less than 5.00, being a nonsmoker or nondrinker, anemia was significantly associated with cognitive dysfunction. Conclusions The findings of the present study suggest the existence of an association between anemia and low cognitive performance among hypertensive elderly. Clinical trial number: not applicable. cognitive dysfunction anemia hypertension the elderly NHANES Figures Figure 1 Figure 2 Figure 3 1. Introduction The global population of individuals aged 65 and above is projected to increase from 771 million in 2022 to 1.6 billion in 2050 ( 1 ). Aging aggravates the prevalence of cognitive impairment ( 2 ). Cognitive dysfunction has gradually become one of the most serious social health problems around the world ( 3 ). It not only causes distress to the patient’s quality of life in everyday functioning and social abilities ( 4 ), but also places an immense burden on families, medical institutions and society ( 5 ). Normal cognitive function is critically dependent on the adequate supply of oxygen and nutrients to neurons through cerebral blood flow ( 6 ). Anemia, the most common blood disorder in the world ( 7 ), reduces blood oxygen content and brain O 2 delivery ( 8 ), therefore may increase the risk of cognitive dysfunction in elderly population. Hypertension is well known to alter in the structure and function of cerebral blood vessels ( 9 ), which may further deteriorate cerebral oxygen and blood supply, leading to cognitive function decline. However, few studies investigate the correlation between anemia and cognitive dysfunction in hypertensive elderly population. In this study, we aimed to explore the association of anemia and cognitive function in elderly patients with hypertension. Data from the National Health and Nutrition Examination Survey (NHANES) conducted between 2011 and 2014 were analyzed. 2. Methods 2.1. Study population The National Health and Nutrition Examination Study (NHANES) is a cross-sectional countrywide study in the United States that can be accessed through the Centers for Disease Control and Prevention National Centre for Health Statistics (NCHS; https://www.cdc.gov/nchs/ ). The study protocol was approved by the NCHS Research Ethics Review Board, and all participants provided written informed consent before participation. In the current study, we used data from the NHANES 2011–2012 and NHANES 2013–2014 cycles. A total of 19,931 participants were enrolled, with 4817 of them diagnosed with hypertension. Hypertension (HTN) was defined when the participants self-reported HTN or used medication for HTN or based on an average systolic blood pressure (BP) ≥ 140 mmHg or/and diastolic BP ≥ 90 mmHg ( 10 ). Among them, 2581 participants aged 60 years or above and 2081 completed the cognitive function questionnaire. After the exclusion of participants without hemoglobin level, 2005 participants were eligible for final analysis (Fig. 1 ). 2.2. Anemia assessment According to the World Health Organization (WHO) diagnostic criteria for anemia and assessment of severity, serum hemoglobin < 12 g/dL in female adults and < 13 g/dL in male adults were identified as anemia patients. Hemoglobin thresholds for categorizing the severity of anemia in females were determined as follows: mild (110–119 g/L), moderate (80–109 g/L), and severe (less than 80 g/L). In males, the corresponding thresholds were mild (110–129 g/L), moderate (80–109 g/L), and severe (less than 80 g/L) ( 11 ). 2.3. Cognitive function Cognitive function was measured by the Consortium to Establish a Registry for Alzheimer’s Disease (CERAD) Word Learning sub-test, the Animal Fluency Test (AFT) and the Digit Symbol Substitution Test (DSST). The CERAD Word List Learning Tests were designed to assess immediate learning ability for new verbal information. The AFT examines categorical verbal fluency in executive function. DSST, a performance module from the Wechsler Adult Intelligence Scale, was used to assess processing speed, sustained attention and working memory. Higher scores on three cognitive tests indicated better cognitive performance. Cognitive function impairment (CFI) was defined as scoring in the lowest 25th percentile on each test. The CFI group received 1 point for each test where they scored in the lowest quartile, and 0 points for scoring in other quartiles. These scores were summed to create the overall CFI scores, with higher scores indicating a more severe cognitive impairment. A CFI score of 0 was defined as normal cognitive function while CFI score of greater than 0 indicated cognitive dysfunction in this study ( 12 – 14 ). 2.4. Covariates Sociodemographic variables were included in this study. Information of age, gender, race (Mexican American, other Hispanics, non-Hispanic white, non-Hispanic black, other races) were gathered. Educational levels of the subjects were classified as below high school, high school or equivalent, and college or above. Family poverty-to-income ratio (PIR) included two states: <5.00 and ≥ 5.00 ( 15 ). Participant’s marital status was categorized into five groups: married, widowed, divorced or separated, never married and living with a partner. Smoking status was classified into three groups: non-smokers (those who smoked < 100 cigarettes in their lifetime), previous smokers (those who had smoked ≥ 100 cigarettes but currently do not smoke) and current smokers (those who had smoked ≥ 100 cigarettes and reported the number of cigarettes smoked per day in the past 30 days) ( 16 ). Alcohol use is assessed by asking participants if they have consumed at least 12 alcohol drinks per year ( 14 ). Body mass index (BMI) was calculated based on height and weight (kg/m 2 ). All these covariates were included in the models as potential confounders and were selected a priori based on previous literature. 2.5. Statistical analysis SPSS 26.0 was used for data analysis. Kolmogorov–Smirnov test was applied to determine whether continuous variables were normally distributed. Continuous data were expressed as mean ± standard deviation (SD) with a normal distribution or as median (interquartile range) with a non-normal distribution and analyzed applying a two-sample independent t test or Mann–Whitney U test. Categorical variables were presented as frequencies (%) and compared using chi-square test or Fisher’s exact test. Multivariate logistic regression models were employed to calculate the odds ratios (ORs) and their corresponding 95% confidence intervals (CIs) for the association between anemia and cognitive dysfunction. Three models were developed. In Model 1, no covariates were adjusted. Model 2 was adjusted for gender, age and race. Model 3 was adjusted for gender, age, race, educational levels, marital status, alcohol use, smoking status, BMI and PIR. Subgroup analyses were conducted based on gender, age, race, educational levels, marital status, alcohol use, smoking status, BMI and PIR to explore the relationship between anemia and cognitive dysfunction. Interaction of the stratified groups were also performed. A two-sided p < 0.05 was considered statistically significant. 2.6. Sensitivity analysis Two sensitivity analyses were conducted to test the stability of the results. First, we enlarged the population group and included all 2800 participants with complete data of cognitive function questionnaire and hemoglobin level. Second, we redefined cognitive dysfunction as the lowest quartile of the total score of three cognition tests and analyzed the association between anemia and cognitive dysfunction ( 17 , 18 ). 3. Results 3.1. Baseline characteristics of participants A total of 19,931 individuals participated in the NHANES during 2011–2014. Among these subjects, 2005 were included in the study after applying the exclusion criteria (Fig. 1 ). The baseline characteristics of all eligible participants were presented in Table 1 . The average age, PIR and BMI of the population were 70.01 ± 6.84 years, 2.54 ± 1.51 and 29.70 ± 6.52 kg/m2, respectively. Of these participants, 53.02% were females and 47.33% were non-Hispanic white. Most participants were married (54.11%) and have a highest degree of education was college or above (48.58%). There is no statistical difference in smoking status between two groups with or without cognitive dysfunction. But two groups differed significantly in alcohol use. Compared with normal cognitive function group, participants with cognitive dysfunction were more likely to be have anemia (Table 1 ). Table 1 General characteristics of participants (n = 2,005) Abbreviations: CD, cognitive dysfunction; BMI, body mass index Characteristics Overall (n = 2005) Normal (n = 942) CD (n = 1063) p Age 70.01 ± 6.84 68.47 ± 6.56 71.38 ± 6.80 0.000 Gender 0.000 Male 942 (46.98) 398 (42.25) 544 (51.18) Female 1063 (53.02) 544 (57.75) 519 (48.82) Race 0.000 Mexican American 164 (8.18) 77 (8.17) 87 (8.18) Other Hispanic 185 (9.23) 54 (5.73) 131 (12.32) Non-Hispanic White 949 (47.33) 537 (57.01) 412 (38.76) Non-Hispanic Black 529 (26.38) 205 (21.76) 324 (30.48) Other Races 178 (8.88) 69 (7.32) 109 (10.25) Education 0.000 <High school 526 (26.23) 110 (11.68) 416 (39.13) High school or equivalent 504 (25.14) 233 (24.73) 271 (25.49) ≥College 974 (48.58) 599 (63.59) 375 (35.28) Poverty income ratio 2.54 ± 1.51 2.93 ± 1.54 2.20 ± 1.41 0.000 Marital status 0.000 Married 1085 (54.11) 548 (58.17) 537 (50.52) Widowed 442 (22.04) 159 (16.88) 283 (26.62) Divorced or separated 312 (15.56) 155 (16.45) 157 (14.77) Never married 117 (5.84) 58 (6.16) 59 (5.55) Living with partner 47 (2 34) 21 (2 23) 26 (2.45) Smoking status 0.438 Current 259 (12.92) 113 (12.00) 146 (13.73) Previous 765 (38.15) 369 (39.17) 396 (37.25) Never 981 (48.93) 460 (48.83) 521 (49.01) Alcohol use 0.001 Yes 1358 (67.73) 671 (71.23) 687 (64.63) No 644 (32.12) 271 (28.77) 373 (35.09) BMI 29.70 ± 6.52 30.21 ± 6.69 29.25 ± 6.34 0.001 Anemic status 0.000 No 1673 (83.44) 838 (88.96) 835 (78.55) Yes 332 (16.56) 104 (11.04) 228 (21.45) 3.2. Association between anemia and cognitive dysfunction Table 2 presents the correlation between anemia and cognitive dysfunction through binary logistic regression analysis. As shown in Model 1, compared with non-anemic participants, those diagnosed with anemia were associated with the greater risk of low cognitive performance [odds ratio (OR) = 2.005, 95% confidence interval (CI: 1.574–2.555)]. After adjusting confounding factors, these findings still existed (Model 2 and Model 3). Participants with mild anemia were more likely to have cognitive dysfunction compared with those without anemia in the fully adjusted model (OR = 1.427, 95% CI:1.065–1.911). Higher level of hemoglobin was associated with lower risk of cognitive dysfunction all three models. In the group of patients with mild anemia, association between hemoglobin level and cognitive dysfunction was significant in adjusted models. Table 2 Associations between anaemia and cognitive dysfunction in hypertensive elderly (n = 2,005) Abbreviation: NA, not available Model 1 p Model 2 p Model 3 p Variable OR (95% CI) OR (95% CI) OR (95% CI) Anaemia 2.005 (1.574–2.555) 0.000 1.500 (1.154–1.951) 0.002 1.462 (1.105–1.936) 0.008 Anaemia cut-offs Mild 1.951 (1.516–2.510) 0.000 1.460 (1.112–1.918) 0.006 1.427 (1.065–1.911) 0.017 Moderate 2.630 (1.238–5.589) 0.012 1.977 (0.877–4.458) 0.100 0.867 (0.802–0.937) 0.151 Haemoglobin level 0.848 (0.797–0.901) 0.000 0.864 (0.803–0.929) 0.000 0.883 (0.817–0.955) 0.002 Non anaemia 0.926 (0.853–1.006) 0.070 0.902 (0.811–1.003) 0.058 0.930 (0.829–1.044) 0.222 Mild anaemia 0.778 (0.555–1.091) 0.146 0.511 (0.316–0.826) 0.006 0.553 (0.331–0.923) 0.024 Moderate anaemia 0.921 (0.309–2.741) 0.882 1.062 (0.327–3.450) 0.920 NA 0.999 3.3. Association between anemia and cognitive dysfunction in different domains Associations between anemia and performance in different cognitive tests were shown in Fig. 2 . There was no statistical disparity observed in the performance of CERAD test between participants with and without anemia. After adjusting for possible confounding factors, anemia was associated with lower performance in AFT and DSST (Table 3 ). Table 3 Associations between anaemia and performance in different cognitive tests Low CERAD p Low AFT p Low DSST p OR (95% CI) OR (95% CI) OR (95% CI) Model 1 1.187 (0.922–1.527) 0.183 1.874 (1.459–2.407) 0.000 2.473 (1.933–3.162) 0.000 Model 2 0.923 (0.704–1.210) 0.562 1.396 (1.069–1.823) 0.014 1.836 (1.399–2.409) 0.000 Model 3 0.856 (0.646–1.134) 0.279 1.331 (1.008–1.758) 0.044 1.818 (1.335–2.475) 0.000 Abbreviations: CERAD, Consortium to Establish a Registry for Alzheimer’s Disease; AFT, animal fluency test; DSST, Digit Symbol Substitution Test 3.4. Subgroup analysis Stratified analyses were performed to evaluate the stability of the relationship between anemia and cognitive dysfunctions. Participants were categorized into different subgroups based on demographic factors and the result was shown in Fig. 3 . The findings revealed that the relationship between anemia and cognitive dysfunction was steady regardless of education level or marital status. In subgroups of age younger than 65 or older than 80 years, being a female, being non-Hispanic White, with poverty income ratio less than 5.00, being a nonsmoker or nondrinker, anemia was significantly associated with cognitive dysfunction. 3.5. Sensitivity analysis Three sensitivity analyses were performed. Firstly, the baseline characteristics of the included sample and all hypertensive elderly above 60 years old were comparable (Table S1 ). Secondly, a total of 2800 participants above 60 years old with and without hypertension were included for analysis. The result showed that in the hypertensive group, anemia was a risk factor of cognitive dysfunction in all three models (Table S2). In non-hypertensive group, anemia was not associated with cognitive dysfunction (Table S3). In addition, we defined cognitive dysfunction based on the total score of three cognition tests, the association between anemia and cognitive dysfunction was still positive (Table S4). 4. Discussion The cross-sectional study showed that anemia was a risk factor of cognitive dysfunction in hypertensive patients. Previous studies showed that anemia and low hemoglobin concentrations are independent risk factors of cognitive decline and increased risk of dementia ( 19 – 21 ). Research has also demonstrated that elevated blood pressure is a well-established risk factor for age-related cognitive decline ( 22 , 23 ). Thus, it can be inferred that individuals with comorbidities of anemia and hypertension may experience a more severe cognitive decline. However, Tamura’s study found that among older adults with chronic kidney disease, more than 90% of whom were diagnosed with hypertension, anemia was not independently associated with baseline cognitive function or decline ( 24 ). Tamura's study comprised 762 participants, the majority of whom were relatively young, with approximately 23% below the age of 60. Consequently, the potential impact of anemia and hypertension on cognitive function may not be readily discernible in this cohort. In the current study, anemia was strongly associated with cognitive dysfunction in hypertensive elderly aging 60 years and above, Participants without hypertension scored significantly higher in three cognitive tests (Table S5). And among general population with or without hypertension, there was an interaction between anemia and hypertension on cognitive dysfunction (Table S6) and anemia was associated with cognitive dysfunction only in hypertensive subgroup. High blood pressure and low hemoglobin can produce additive negative effect on cognitive function in elderly population. Thus, more attention should be paid for anemic elderly, especially those with hypertension. Avraham Weiss’s research recruited 36,951 community-dwelling elders and showed that the more severe the anemia, the greater the risk of developing dementia and cognitive decline during the 10-year follow-up period ( 20 ). However, another large cohort study with a total of 13,624 participants concluded that anemia and hemoglobin levels were not associated with worse performance in either global or separate cognitive tests ( 25 ). In this study, only hypertensive elderly were included. We found that the association of mild anemia and cognitive dysfunction was significant. Also, a notable association was observed between hemoglobin levels and cognitive impairment within the cohort exhibiting mild anemia. The limited number of subjects with moderate anemia (n = 32) precluded a separate analysis of its impact on cognitive function. In the elderly, the importance of mild anemia has been neglected for a long time ( 26 ). Moderate and severe anemia are conditions that arise patients’ attention due to more pronounced clinical manifestations. But mild anemia is more easily overlooked and tolerated that can eventually lead to chronic cerebral hypoxia or even tissue damage. So, even a mild anemia may substantially affect physical and cognitive capacities, as well as overall quality of life ( 27 ). Therefore, for hypertensive elderly, hemoglobin level should be regarded as a routine medical examination. Early identification and subsequent treatment of even mild anemia may have a positive effect on cognition improvement. The association pattern found in this current study suggests that the deleterious effect of anemia and hypertension on the cognitive function may be more substantial on executive function, attention, and working memory domains (AFT and DSST), instead of learning (CERAD) in elderly participants. Schneider’s research found that anemia subtypes were associated similarly with cognition, with strongest associations for the digit symbol substitution test (DSST), compared with delayed word recall test (DWRT), and word fluency test (WFT) ( 28 ). Hestad’s study also showed that Digit Symbol Substitution Test performance most strongly associated with blood pressure instead of the Mini Mental State Examination (MMSE) and the Twelve-word Test ( 29 ). In this study, among elderly diagnosed with hypertension, association of anemia and low DSST score was most obvious after full adjustment, which was consistent with results of previous studies. The Digit Symbol Test, which is related to processing speed and attention, is considered to be a highly sensitive test for brain damage, even when the damage is minimal ( 29 , 30 ). It has been widely used to evaluate global cognitive function in individuals aged 60 years and older ( 31 , 32 ). So, DSST may be used as a screening tool for patients with both hypertension and anemia for early diagnosis of cognitive dysfunction, although the sensitivity and specificity of this test require future exploration. Previous studies showed that the association of anemia with dementia and cognitive decline was similar in both men and women ( 19 , 20 ). However, there were some controversial results. Dlugaj’s research found that the association of anemia and mild cognitive impairment was more pronounced in men than in women ( 33 ). Furthermore, the PRO.V.A study found that the potential value of a low hemoglobin concentration to predict cognitive impairment was more pronounced in males as opposed to females ( 34 ). In the current study, we found that although fewer female than male participants were diagnosed with anemia (14.86% in female vs 18.47% in male, P = 0.03), the correlation between anemia and cognitive dysfunction was found to be statistically significant in the subgroup of hypertensive females rather than males. We also found that the average systolic blood pressure was significantly higher in female (138.56 ± 20.57mmHg for female vs 136.57 ± 19.49mmHg for male, P = 0.03). Therefore, systolic blood pressure may serve as a more significant predictor for cognitive impairment in females, as evidenced by the findings of Hestad’ team, who specifically found that unlike men, women in the older age groups (65–74 years) exhibited a strong association between higher systolic blood pressure and poorer performance on the Digit Symbol Test ( 29 ). Previous study demonstrated that advanced age, high blood pressure, and anemia were individually correlated with cognitive dysfunction ( 2 , 9 , 20 ). Furthermore, the combination of these three risk factors led to a notable decline in cognitive function, particularly evident in elderly individuals aged 80 years and above with hypertension and anemia as shown in this study. However, we also found that anemia was associated with cognitive dysfunction in age group younger than 65 years old. One possible explanation is that younger individuals may have higher cerebral oxygen demand, which could be negatively impacted by insufficient hemoglobin supply, leading to impaired cognitive function. Detailed mechanisms of anemia on cerebral pathophysiologic changes in different age group require further exploration. For hypertensive patients with PIR lower than 5.0, anemia was associated with cognitive dysfunction, indicating that this population group was more vulnerable to anemia probably due to poor awareness of health problems and indifference to low hemoglobin level. We also found that the association of anemia and cognitive dysfunction was significant in non-Hispanic White (n = 949), but not in other races, which was probably due to relatively small number of participants in other ethnic groups. Smoking and alcohol were considered potential risk factors for cognitive decline ( 35 – 38 ). In this study, among never smokers and non-drinkers, anemia was significantly associated with cognitive decline. Therefore, even in patients with relatively healthy lifestyle, prevention and treatment of anemia may play a positive role on cognition preservation. The interaction between anemia and BMI on cognitive dysfunction was statistically significant, but no significant subgroups were found when dividing the population based on current international overweight and obesity classifications ( 39 ). Further research on different BMI categorizations that is also clinically valuable is worth investigation in the future. However, there are some limitations in this study. First, its cross-sectional design hinders the establishment of a causal relationship between anemia and cognitive dysfunction. Future cohort studies or randomized controlled clinical trials may help address this limitation. Second, unknown confounding factors were not completely adjusted in logistic regression, such as types and dosage of medication. Last but not least, while multiple tests were utilized to assess cognitive function, the findings may not fully capture overall cognitive abilities. 5. Conclusions The findings of the present study suggest the existence of an association between anemia and low cognitive performance among hypertensive elderly. More attention should be paid on anemia prevention and treatment in older population with hypertension for preservation of cognitive function Declarations Acknowledgments We sincerely thank the researchers and participants of NHANES for data collection and management of data resources. Author contributions All authors confirmed their approval for the manuscript to be published. Study concept and design: LL and QX. Acquisition of subjects and/or data: JH and XL. Analysis and interpretation of data: LL. Preparation of manuscript: QX. Funding Not applicable. Data availability The data used in this study can be downloaded for free in NHANES. https://wwwn.cdc.gov/nchs/nhanes/Default.aspx. Further inquiries can be directed to the corresponding author. Ethics approval and consent to participate The studies involving human participants were reviewed and approved through the NHANES has been approved through the National Center for Health Statistics Research Ethics Review Board. All participants have provided their informed consent. Consent for publication The authors are consent for publication. Competing interests All authors declare no potential conflict of interest. References Wang N, Wang L, Wang J et al. Effects of physical activity and depressive symptoms on cognitive function in older adults: National Health and Nutrition Examination Survey. Neurol Sci. 2024 Jan;45(1):299-308. doi: 10.1007/s10072-023-07250-5. Boyle PA, Wang T, Yu L el al. The "cognitive clock": A novel indicator of brain health. 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A Network Meta-Analysis Comparing Effects of Various Antidepressant Classes on the Digit Symbol Substitution Test (DSST) as a Measure of Cognitive Dysfunction in Patients with Major Depressive Disorder. Int J Neuropsychopharmacol. 2018 Feb 1;21(2):97-107. doi: 10.1093/ijnp/pyx070. Dlugaj M, Winkler A, Weimar C et al. Anemia and Mild Cognitive Impairment in the German General Population. J Alzheimers Dis. 2016;49(4):1031-42. doi: 10.3233/JAD-150434. Trevisan C, Veronese N, Bolzetta F et al. Low Hemoglobin Levels and the Onset of Cognitive Impairment in Older People: The PRO.V.A. Study. Rejuvenation Res. 2016 Dec;19(6):447-55. doi: 10.1089/rej.2015.1768. Hay M, Barnes C, Huentelman M, Brinton R, Ryan L. Hypertension and Age-Related Cognitive Impairment: Common Risk Factors and a Role for Precision Aging. Curr Hypertens Rep. 2020 Sep 3;22(10):80. doi: 10.1007/s11906-020-01090-w. Rajczyk JI, Ferketich A, Wing JJ. Relation Between Smoking Status and Subjective Cognitive Decline in Middle Age and Older Adults: A Cross-Sectional Analysis of 2019 Behavioral Risk Factor Surveillance System Data. J Alzheimers Dis. 2023;91(1):215-23. doi: 10.3233/JAD-220501. Koch M, Fitzpatrick AL, Rapp SR et al. Alcohol Consumption and Risk of Dementia and Cognitive Decline Among Older Adults With or Without Mild Cognitive Impairment. JAMA Netw Open. 2019 Sep 4;2(9):e1910319. doi: 10.1001/jamanetworkopen.2019.10319. Cui Y, Si W, Zhu C, Zhao Q. Alcohol Consumption and Mild Cognitive Impairment: A Mendelian Randomization Study from Rural China. Nutrients. 2022 Aug 31;14(17):3596. doi: 10.3390/nu14173596. Kompaniyets L, Freedman DS, Belay B et al. Probability of 5% or Greater Weight Loss or BMI Reduction to Healthy Weight Among Adults With Overweight or Obesity. JAMA Netw Open. 2023 Aug 1;6(8):e2327358. doi: 10.1001/jamanetworkopen.2023.27358. Additional Declarations No competing interests reported. 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Introduction","content":"\u003cp\u003eThe global population of individuals aged 65 and above is projected to increase from 771\u0026nbsp;million in 2022 to 1.6\u0026nbsp;billion in 2050 (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Aging aggravates the prevalence of cognitive impairment (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Cognitive dysfunction has gradually become one of the most serious social health problems around the world (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). It not only causes distress to the patient\u0026rsquo;s quality of life in everyday functioning and social abilities (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e), but also places an immense burden on families, medical institutions and society (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eNormal cognitive function is critically dependent on the adequate supply of oxygen and nutrients to neurons through cerebral blood flow (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Anemia, the most common blood disorder in the world (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e), reduces blood oxygen content and brain O\u003csub\u003e2\u003c/sub\u003e delivery (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e), therefore may increase the risk of cognitive dysfunction in elderly population. Hypertension is well known to alter in the structure and function of cerebral blood vessels (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e), which may further deteriorate cerebral oxygen and blood supply, leading to cognitive function decline. However, few studies investigate the correlation between anemia and cognitive dysfunction in hypertensive elderly population.\u003c/p\u003e \u003cp\u003eIn this study, we aimed to explore the association of anemia and cognitive function in elderly patients with hypertension. Data from the National Health and Nutrition Examination Survey (NHANES) conducted between 2011 and 2014 were analyzed.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Study population\u003c/h2\u003e \u003cp\u003eThe National Health and Nutrition Examination Study (NHANES) is a cross-sectional countrywide study in the United States that can be accessed through the Centers for Disease Control and Prevention National Centre for Health Statistics (NCHS; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.cdc.gov/nchs/\u003c/span\u003e\u003cspan address=\"https://www.cdc.gov/nchs/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The study protocol was approved by the NCHS Research Ethics Review Board, and all participants provided written informed consent before participation.\u003c/p\u003e \u003cp\u003eIn the current study, we used data from the NHANES 2011\u0026ndash;2012 and NHANES 2013\u0026ndash;2014 cycles. A total of 19,931 participants were enrolled, with 4817 of them diagnosed with hypertension. Hypertension (HTN) was defined when the participants self-reported HTN or used medication for HTN or based on an average systolic blood pressure (BP)\u0026thinsp;\u0026ge;\u0026thinsp;140 mmHg or/and diastolic BP\u0026thinsp;\u0026ge;\u0026thinsp;90 mmHg (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Among them, 2581 participants aged 60 years or above and 2081 completed the cognitive function questionnaire. After the exclusion of participants without hemoglobin level, 2005 participants were eligible for final analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Anemia assessment\u003c/h2\u003e \u003cp\u003eAccording to the World Health Organization (WHO) diagnostic criteria for anemia and assessment of severity, serum hemoglobin\u0026thinsp;\u0026lt;\u0026thinsp;12 g/dL in female adults and \u0026lt;\u0026thinsp;13 g/dL in male adults were identified as anemia patients. Hemoglobin thresholds for categorizing the severity of anemia in females were determined as follows: mild (110\u0026ndash;119 g/L), moderate (80\u0026ndash;109 g/L), and severe (less than 80 g/L). In males, the corresponding thresholds were mild (110\u0026ndash;129 g/L), moderate (80\u0026ndash;109 g/L), and severe (less than 80 g/L) (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Cognitive function\u003c/h2\u003e \u003cp\u003eCognitive function was measured by the Consortium to Establish a Registry for Alzheimer\u0026rsquo;s Disease (CERAD) Word Learning sub-test, the Animal Fluency Test (AFT) and the Digit Symbol Substitution Test (DSST). The CERAD Word List Learning Tests were designed to assess immediate learning ability for new verbal information. The AFT examines categorical verbal fluency in executive function. DSST, a performance module from the Wechsler Adult Intelligence Scale, was used to assess processing speed, sustained attention and working memory. Higher scores on three cognitive tests indicated better cognitive performance. Cognitive function impairment (CFI) was defined as scoring in the lowest 25th percentile on each test. The CFI group received 1 point for each test where they scored in the lowest quartile, and 0 points for scoring in other quartiles. These scores were summed to create the overall CFI scores, with higher scores indicating a more severe cognitive impairment. A CFI score of 0 was defined as normal cognitive function while CFI score of greater than 0 indicated cognitive dysfunction in this study (\u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Covariates\u003c/h2\u003e \u003cp\u003eSociodemographic variables were included in this study. Information of age, gender, race (Mexican American, other Hispanics, non-Hispanic white, non-Hispanic black, other races) were gathered. Educational levels of the subjects were classified as below high school, high school or equivalent, and college or above. Family poverty-to-income ratio (PIR) included two states: \u0026lt;5.00 and \u0026ge;\u0026thinsp;5.00 (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Participant\u0026rsquo;s marital status was categorized into five groups: married, widowed, divorced or separated, never married and living with a partner. Smoking status was classified into three groups: non-smokers (those who smoked\u0026thinsp;\u0026lt;\u0026thinsp;100 cigarettes in their lifetime), previous smokers (those who had smoked\u0026thinsp;\u0026ge;\u0026thinsp;100 cigarettes but currently do not smoke) and current smokers (those who had smoked\u0026thinsp;\u0026ge;\u0026thinsp;100 cigarettes and reported the number of cigarettes smoked per day in the past 30 days) (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Alcohol use is assessed by asking participants if they have consumed at least 12 alcohol drinks per year (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). Body mass index (BMI) was calculated based on height and weight (kg/m\u003csup\u003e2\u003c/sup\u003e). All these covariates were included in the models as potential confounders and were selected a priori based on previous literature.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5. Statistical analysis\u003c/h2\u003e \u003cp\u003eSPSS 26.0 was used for data analysis. Kolmogorov\u0026ndash;Smirnov test was applied to determine whether continuous variables were normally distributed. Continuous data were expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD) with a normal distribution or as median (interquartile range) with a non-normal distribution and analyzed applying a two-sample independent t test or Mann\u0026ndash;Whitney U test. Categorical variables were presented as frequencies (%) and compared using chi-square test or Fisher\u0026rsquo;s exact test.\u003c/p\u003e \u003cp\u003eMultivariate logistic regression models were employed to calculate the odds ratios (ORs) and their corresponding 95% confidence intervals (CIs) for the association between anemia and cognitive dysfunction. Three models were developed. In Model 1, no covariates were adjusted. Model 2 was adjusted for gender, age and race. Model 3 was adjusted for gender, age, race, educational levels, marital status, alcohol use, smoking status, BMI and PIR.\u003c/p\u003e \u003cp\u003eSubgroup analyses were conducted based on gender, age, race, educational levels, marital status, alcohol use, smoking status, BMI and PIR to explore the relationship between anemia and cognitive dysfunction. Interaction of the stratified groups were also performed. A two-sided p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6. Sensitivity analysis\u003c/h2\u003e \u003cp\u003eTwo sensitivity analyses were conducted to test the stability of the results. First, we enlarged the population group and included all 2800 participants with complete data of cognitive function questionnaire and hemoglobin level. Second, we redefined cognitive dysfunction as the lowest quartile of the total score of three cognition tests and analyzed the association between anemia and cognitive dysfunction (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Baseline characteristics of participants\u003c/h2\u003e \u003cp\u003eA total of 19,931 individuals participated in the NHANES during 2011\u0026ndash;2014. Among these subjects, 2005 were included in the study after applying the exclusion criteria (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The baseline characteristics of all eligible participants were presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The average age, PIR and BMI of the population were 70.01\u0026thinsp;\u0026plusmn;\u0026thinsp;6.84 years, 2.54\u0026thinsp;\u0026plusmn;\u0026thinsp;1.51 and 29.70\u0026thinsp;\u0026plusmn;\u0026thinsp;6.52 kg/m2, respectively. Of these participants, 53.02% were females and 47.33% were non-Hispanic white. Most participants were married (54.11%) and have a highest degree of education was college or above (48.58%). There is no statistical difference in smoking status between two groups with or without cognitive dysfunction. But two groups differed significantly in alcohol use. Compared with normal cognitive function group, participants with cognitive dysfunction were more likely to be have anemia (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\u003eGeneral characteristics of participants (n\u0026thinsp;=\u0026thinsp;2,005) Abbreviations: CD, cognitive dysfunction; BMI, body mass index\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;2005)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;942)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCD\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;1063)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e70.01\u0026thinsp;\u0026plusmn;\u0026thinsp;6.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e68.47\u0026thinsp;\u0026plusmn;\u0026thinsp;6.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e71.38\u0026thinsp;\u0026plusmn;\u0026thinsp;6.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\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=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e942 (46.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e398 (42.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e544 (51.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1063 (53.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e544 (57.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e519 (48.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRace\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\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=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMexican American\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e164 (8.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e77 (8.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e87 (8.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther Hispanic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e185 (9.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54 (5.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e131 (12.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-Hispanic White\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e949 (47.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e537 (57.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e412 (38.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-Hispanic Black\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e529 (26.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e205 (21.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e324 (30.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther Races\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e178 (8.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e69 (7.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e109 (10.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\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=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;High school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e526 (26.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e110 (11.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e416 (39.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh school or equivalent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e504 (25.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e233 (24.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e271 (25.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;College\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e974 (48.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e599 (63.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e375 (35.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePoverty income ratio\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.54\u0026thinsp;\u0026plusmn;\u0026thinsp;1.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.93\u0026thinsp;\u0026plusmn;\u0026thinsp;1.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.20\u0026thinsp;\u0026plusmn;\u0026thinsp;1.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMarital status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\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=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1085 (54.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e548 (58.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e537 (50.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWidowed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e442 (22.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e159 (16.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e283 (26.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDivorced or separated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e312 (15.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e155 (16.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e157 (14.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNever married\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e117 (5.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58 (6.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e59 (5.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiving with partner\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e47 (2 34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21 (2 23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26 (2.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSmoking status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\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=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.438\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCurrent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e259 (12.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e113 (12.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e146 (13.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrevious\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e765 (38.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e369 (39.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e396 (37.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNever\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e981 (48.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e460 (48.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e521 (49.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAlcohol use\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\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=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1358 (67.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e671 (71.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e687 (64.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e644 (32.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e271 (28.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e373 (35.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBMI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29.70\u0026thinsp;\u0026plusmn;\u0026thinsp;6.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30.21\u0026thinsp;\u0026plusmn;\u0026thinsp;6.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29.25\u0026thinsp;\u0026plusmn;\u0026thinsp;6.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAnemic status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\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=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1673 (83.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e838 (88.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e835 (78.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e332 (16.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e104 (11.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e228 (21.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\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=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Association between anemia and cognitive dysfunction\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e presents the correlation between anemia and cognitive dysfunction through binary logistic regression analysis. As shown in Model 1, compared with non-anemic participants, those diagnosed with anemia were associated with the greater risk of low cognitive performance [odds ratio (OR)\u0026thinsp;=\u0026thinsp;2.005, 95% confidence interval (CI: 1.574\u0026ndash;2.555)]. After adjusting confounding factors, these findings still existed (Model 2 and Model 3). Participants with mild anemia were more likely to have cognitive dysfunction compared with those without anemia in the fully adjusted model (OR\u0026thinsp;=\u0026thinsp;1.427, 95% CI:1.065\u0026ndash;1.911). Higher level of hemoglobin was associated with lower risk of cognitive dysfunction all three models. In the group of patients with mild anemia, association between hemoglobin level and cognitive dysfunction was significant in adjusted models.\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\u003eAssociations between anaemia and cognitive dysfunction in hypertensive elderly (n\u0026thinsp;=\u0026thinsp;2,005) Abbreviation: NA, not available\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" 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=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModel 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModel 2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eModel 3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAnaemia\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.005 (1.574\u0026ndash;2.555)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.000\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.500 (1.154\u0026ndash;1.951)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.462 (1.105\u0026ndash;1.936)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.008\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAnaemia cut-offs\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMild\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.951 (1.516\u0026ndash;2.510)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.000\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.460 (1.112\u0026ndash;1.918)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.006\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.427 (1.065\u0026ndash;1.911)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.017\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eModerate\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.630 (1.238\u0026ndash;5.589)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.012\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.977 (0.877\u0026ndash;4.458)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.867 (0.802\u0026ndash;0.937)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.151\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHaemoglobin level\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.848 (0.797\u0026ndash;0.901)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.000\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.864 (0.803\u0026ndash;0.929)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.000\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.883 (0.817\u0026ndash;0.955)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNon anaemia\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.926 (0.853\u0026ndash;1.006)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.070\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.902 (0.811\u0026ndash;1.003)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.058\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.930 (0.829\u0026ndash;1.044)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.222\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMild anaemia\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.778 (0.555\u0026ndash;1.091)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.146\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.511 (0.316\u0026ndash;0.826)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.006\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.553 (0.331\u0026ndash;0.923)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.024\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eModerate anaemia\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.921 (0.309\u0026ndash;2.741)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.882\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.062 (0.327\u0026ndash;3.450)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.920\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.999\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 \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Association between anemia and cognitive dysfunction in different domains\u003c/h2\u003e \u003cp\u003eAssociations between anemia and performance in different cognitive tests were shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. There was no statistical disparity observed in the performance of CERAD test between participants with and without anemia. After adjusting for possible confounding factors, anemia was associated with lower performance in AFT and DSST (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociations between anaemia and performance in different cognitive tests\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow CERAD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLow AFT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLow DSST\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eModel 1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.187 (0.922\u0026ndash;1.527)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.183\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.874 (1.459\u0026ndash;2.407)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.000\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.473 (1.933\u0026ndash;3.162)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.000\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eModel 2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.923 (0.704\u0026ndash;1.210)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.562\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.396 (1.069\u0026ndash;1.823)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.014\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.836 (1.399\u0026ndash;2.409)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.000\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eModel 3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.856 (0.646\u0026ndash;1.134)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.279\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.331 (1.008\u0026ndash;1.758)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.044\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.818 (1.335\u0026ndash;2.475)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.000\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eAbbreviations: CERAD, Consortium to Establish a Registry for Alzheimer\u0026rsquo;s Disease; AFT, animal fluency test; DSST, Digit Symbol Substitution Test\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.4. Subgroup analysis\u003c/h2\u003e \u003cp\u003eStratified analyses were performed to evaluate the stability of the relationship between anemia and cognitive dysfunctions. Participants were categorized into different subgroups based on demographic factors and the result was shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. The findings revealed that the relationship between anemia and cognitive dysfunction was steady regardless of education level or marital status. In subgroups of age younger than 65 or older than 80 years, being a female, being non-Hispanic White, with poverty income ratio less than 5.00, being a nonsmoker or nondrinker, anemia was significantly associated with cognitive dysfunction.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.5. Sensitivity analysis\u003c/h2\u003e \u003cp\u003eThree sensitivity analyses were performed. Firstly, the baseline characteristics of the included sample and all hypertensive elderly above 60 years old were comparable (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Secondly, a total of 2800 participants above 60 years old with and without hypertension were included for analysis. The result showed that in the hypertensive group, anemia was a risk factor of cognitive dysfunction in all three models (Table S2). In non-hypertensive group, anemia was not associated with cognitive dysfunction (Table S3). In addition, we defined cognitive dysfunction based on the total score of three cognition tests, the association between anemia and cognitive dysfunction was still positive (Table S4).\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThe cross-sectional study showed that anemia was a risk factor of cognitive dysfunction in hypertensive patients. Previous studies showed that anemia and low hemoglobin concentrations are independent risk factors of cognitive decline and increased risk of dementia (\u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). Research has also demonstrated that elevated blood pressure is a well-established risk factor for age-related cognitive decline (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). Thus, it can be inferred that individuals with comorbidities of anemia and hypertension may experience a more severe cognitive decline. However, Tamura\u0026rsquo;s study found that among older adults with chronic kidney disease, more than 90% of whom were diagnosed with hypertension, anemia was not independently associated with baseline cognitive function or decline (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). Tamura's study comprised 762 participants, the majority of whom were relatively young, with approximately 23% below the age of 60. Consequently, the potential impact of anemia and hypertension on cognitive function may not be readily discernible in this cohort. In the current study, anemia was strongly associated with cognitive dysfunction in hypertensive elderly aging 60 years and above, Participants without hypertension scored significantly higher in three cognitive tests (Table S5). And among general population with or without hypertension, there was an interaction between anemia and hypertension on cognitive dysfunction (Table S6) and anemia was associated with cognitive dysfunction only in hypertensive subgroup. High blood pressure and low hemoglobin can produce additive negative effect on cognitive function in elderly population. Thus, more attention should be paid for anemic elderly, especially those with hypertension.\u003c/p\u003e \u003cp\u003eAvraham Weiss\u0026rsquo;s research recruited 36,951 community-dwelling elders and showed that the more severe the anemia, the greater the risk of developing dementia and cognitive decline during the 10-year follow-up period (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). However, another large cohort study with a total of 13,624 participants concluded that anemia and hemoglobin levels were not associated with worse performance in either global or separate cognitive tests (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). In this study, only hypertensive elderly were included. We found that the association of mild anemia and cognitive dysfunction was significant. Also, a notable association was observed between hemoglobin levels and cognitive impairment within the cohort exhibiting mild anemia. The limited number of subjects with moderate anemia (n\u0026thinsp;=\u0026thinsp;32) precluded a separate analysis of its impact on cognitive function. In the elderly, the importance of mild anemia has been neglected for a long time (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). Moderate and severe anemia are conditions that arise patients\u0026rsquo; attention due to more pronounced clinical manifestations. But mild anemia is more easily overlooked and tolerated that can eventually lead to chronic cerebral hypoxia or even tissue damage. So, even a mild anemia may substantially affect physical and cognitive capacities, as well as overall quality of life (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). Therefore, for hypertensive elderly, hemoglobin level should be regarded as a routine medical examination. Early identification and subsequent treatment of even mild anemia may have a positive effect on cognition improvement.\u003c/p\u003e \u003cp\u003eThe association pattern found in this current study suggests that the deleterious effect of anemia and hypertension on the cognitive function may be more substantial on executive function, attention, and working memory domains (AFT and DSST), instead of learning (CERAD) in elderly participants. Schneider\u0026rsquo;s research found that anemia subtypes were associated similarly with cognition, with strongest associations for the digit symbol substitution test (DSST), compared with delayed word recall test (DWRT), and word fluency test (WFT) (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). Hestad\u0026rsquo;s study also showed that Digit Symbol Substitution Test performance most strongly associated with blood pressure instead of the Mini Mental State Examination (MMSE) and the Twelve-word Test (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). In this study, among elderly diagnosed with hypertension, association of anemia and low DSST score was most obvious after full adjustment, which was consistent with results of previous studies. The Digit Symbol Test, which is related to processing speed and attention, is considered to be a highly sensitive test for brain damage, even when the damage is minimal (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). It has been widely used to evaluate global cognitive function in individuals aged 60 years and older (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). So, DSST may be used as a screening tool for patients with both hypertension and anemia for early diagnosis of cognitive dysfunction, although the sensitivity and specificity of this test require future exploration.\u003c/p\u003e \u003cp\u003ePrevious studies showed that the association of anemia with dementia and cognitive decline was similar in both men and women (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). However, there were some controversial results. Dlugaj\u0026rsquo;s research found that the association of anemia and mild cognitive impairment was more pronounced in men than in women (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). Furthermore, the PRO.V.A study found that the potential value of a low hemoglobin concentration to predict cognitive impairment was more pronounced in males as opposed to females (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). In the current study, we found that although fewer female than male participants were diagnosed with anemia (14.86% in female vs 18.47% in male, P\u0026thinsp;=\u0026thinsp;0.03), the correlation between anemia and cognitive dysfunction was found to be statistically significant in the subgroup of hypertensive females rather than males. We also found that the average systolic blood pressure was significantly higher in female (138.56\u0026thinsp;\u0026plusmn;\u0026thinsp;20.57mmHg for female vs 136.57\u0026thinsp;\u0026plusmn;\u0026thinsp;19.49mmHg for male, P\u0026thinsp;=\u0026thinsp;0.03). Therefore, systolic blood pressure may serve as a more significant predictor for cognitive impairment in females, as evidenced by the findings of Hestad\u0026rsquo; team, who specifically found that unlike men, women in the older age groups (65\u0026ndash;74 years) exhibited a strong association between higher systolic blood pressure and poorer performance on the Digit Symbol Test (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePrevious study demonstrated that advanced age, high blood pressure, and anemia were individually correlated with cognitive dysfunction (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). Furthermore, the combination of these three risk factors led to a notable decline in cognitive function, particularly evident in elderly individuals aged 80 years and above with hypertension and anemia as shown in this study. However, we also found that anemia was associated with cognitive dysfunction in age group younger than 65 years old. One possible explanation is that younger individuals may have higher cerebral oxygen demand, which could be negatively impacted by insufficient hemoglobin supply, leading to impaired cognitive function. Detailed mechanisms of anemia on cerebral pathophysiologic changes in different age group require further exploration.\u003c/p\u003e \u003cp\u003eFor hypertensive patients with PIR lower than 5.0, anemia was associated with cognitive dysfunction, indicating that this population group was more vulnerable to anemia probably due to poor awareness of health problems and indifference to low hemoglobin level. We also found that the association of anemia and cognitive dysfunction was significant in non-Hispanic White (n\u0026thinsp;=\u0026thinsp;949), but not in other races, which was probably due to relatively small number of participants in other ethnic groups.\u003c/p\u003e \u003cp\u003eSmoking and alcohol were considered potential risk factors for cognitive decline (\u003cspan additionalcitationids=\"CR36 CR37\" citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e). In this study, among never smokers and non-drinkers, anemia was significantly associated with cognitive decline. Therefore, even in patients with relatively healthy lifestyle, prevention and treatment of anemia may play a positive role on cognition preservation.\u003c/p\u003e \u003cp\u003eThe interaction between anemia and BMI on cognitive dysfunction was statistically significant, but no significant subgroups were found when dividing the population based on current international overweight and obesity classifications (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e). Further research on different BMI categorizations that is also clinically valuable is worth investigation in the future.\u003c/p\u003e \u003cp\u003eHowever, there are some limitations in this study. First, its cross-sectional design hinders the establishment of a causal relationship between anemia and cognitive dysfunction. Future cohort studies or randomized controlled clinical trials may help address this limitation. Second, unknown confounding factors were not completely adjusted in logistic regression, such as types and dosage of medication. Last but not least, while multiple tests were utilized to assess cognitive function, the findings may not fully capture overall cognitive abilities.\u003c/p\u003e"},{"header":"5. Conclusions","content":"\u003cp\u003eThe findings of the present study suggest the existence of an association between anemia and low cognitive performance among hypertensive elderly. More attention should be paid on anemia prevention and treatment in older population with hypertension for preservation of cognitive function\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe sincerely thank the researchers and participants of NHANES for data\u0026nbsp;collection and\u0026nbsp;management of data resources.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors confirmed their approval for the manuscript to be published. Study concept and design: LL and QX. Acquisition of subjects and/or data: JH and XL. Analysis and interpretation of data: LL. Preparation of manuscript: QX.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eavailability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data used in this study can be downloaded for free in NHANES. https://wwwn.cdc.gov/nchs/nhanes/Default.aspx. Further inquiries can be directed to the corresponding author.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe studies involving human participants were reviewed and approved through the NHANES has been approved through the National Center for Health Statistics Research Ethics Review Board. All participants have provided their informed consent.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors are consent for publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors declare no potential conflict of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eWang N, Wang L, Wang J et al. Effects of physical activity and depressive symptoms on cognitive function in older adults: National Health and Nutrition Examination Survey. Neurol Sci. 2024 Jan;45(1):299-308. doi: 10.1007/s10072-023-07250-5.\u003c/li\u003e\n \u003cli\u003eBoyle PA, Wang T, Yu L el al. The \u0026quot;cognitive clock\u0026quot;: A novel indicator of brain health. Alzheimers Dement. 2021 Dec;17(12):1923-37. doi: 10.1002/alz.12351.\u003c/li\u003e\n \u003cli\u003eZhou L. 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Developing and validating a nomogram for cognitive impairment in the older people based on the NHANES. Front Neurosci. 2023 Aug 17;17:1195570. doi: 10.3389/fnins.2023.1195570.\u003c/li\u003e\n \u003cli\u003eXie Q, Nie M, Zhang F et al. An unexpected interaction between diabetes and cardiovascular diseases on cognitive function: A cross-sectional study. J Affect Disord. 2024 Jun 1;354:688-93. doi: 10.1016/j.jad.2024.03.040.\u003c/li\u003e\n \u003cli\u003eWang J, Wang C, Li X et al. Association of Anemia with Cognitive Function and Dementia Among Older Adults: The Role of Inflammation. J Alzheimers Dis. 2023;96(1):125-34. doi: 10.3233/JAD-230483.\u003c/li\u003e\n \u003cli\u003eWeiss A, Beloosesky Y, Gingold-Belfer R et al. Association of Anemia with Dementia and Cognitive Decline among Community-Dwelling Elderly. Gerontology. 2022;68(12):1375-83. doi: 10.1159/000522500.\u003c/li\u003e\n \u003cli\u003eQin T, Yan M, Fu Z et al. 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Relation Between Smoking Status and Subjective Cognitive Decline in Middle Age and Older Adults: A Cross-Sectional Analysis of 2019 Behavioral Risk Factor Surveillance System Data. J Alzheimers Dis. 2023;91(1):215-23. doi: 10.3233/JAD-220501.\u003c/li\u003e\n \u003cli\u003eKoch M, Fitzpatrick AL, Rapp SR et al. Alcohol Consumption and Risk of Dementia and Cognitive Decline Among Older Adults With or Without Mild Cognitive Impairment. JAMA Netw Open. 2019 Sep 4;2(9):e1910319. doi: 10.1001/jamanetworkopen.2019.10319. \u0026nbsp;\u003c/li\u003e\n \u003cli\u003eCui Y, Si W, Zhu C, Zhao Q. Alcohol Consumption and Mild Cognitive Impairment: A Mendelian Randomization Study from Rural China. Nutrients. 2022 Aug 31;14(17):3596. doi: 10.3390/nu14173596.\u003c/li\u003e\n \u003cli\u003eKompaniyets L, Freedman DS, Belay B et al. Probability of 5% or Greater Weight Loss or BMI Reduction to Healthy Weight Among Adults With Overweight or Obesity. JAMA Netw Open. 2023 Aug 1;6(8):e2327358. doi: 10.1001/jamanetworkopen.2023.27358.\u003c/li\u003e\n\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":"cognitive dysfunction, anemia, hypertension, the elderly, NHANES","lastPublishedDoi":"10.21203/rs.3.rs-5470638/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5470638/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCognitive dysfunction has become one of the most serious social health problems around the world. Anemia may increase the risk of cognitive dysfunction in elderly population. Hypertension may also deteriorate cognitive function. Few studies reported the association of anemia and cognitive dysfunction in hypertensive elderly.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData were obtained from the 2011–2014 National Health and Nutrition Examination Survey (NHANES). Cognitive performance was evaluated by the Consortium to Establish a Registry for Alzheimer’s Disease (CERAD) Word Learning subtest, the Animal Fluency Test (AFT), and the Digit Symbol Substitution Test (DSST). Multivariate logistic regression analysis and subgroup analysis were conducted to assess the relationship between anemia and cognitive dysfunction.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 2005 elderly participants (aged ≥ 60 years) were included. Anemia was associated with the greater risk of low cognitive performance in hypertensive elderly (OR = 1.427, 95% CI: 1.065–1.911). Anemia was associated with lower performance in AFT (OR = 1.331, 95% CI: 1.008–1.758) and DSST (OR = 1.818, 95% CI: 1.335–2.475). In subgroups of age younger than 65 or older than 80 years, being a female, being non-Hispanic White, with poverty income ratio less than 5.00, being a nonsmoker or nondrinker, anemia was significantly associated with cognitive dysfunction.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe findings of the present study suggest the existence of an association between anemia and low cognitive performance among hypertensive elderly.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number:\u003c/strong\u003e not applicable.\u003c/p\u003e","manuscriptTitle":"Association between anemia and cognitive dysfunction in the hypertensive elderly: a cross-sectional study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-12-19 12:53:45","doi":"10.21203/rs.3.rs-5470638/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":"803b2cfe-86df-4588-8c29-77606b49960d","owner":[],"postedDate":"December 19th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-08-11T04:08:30+00:00","versionOfRecord":[],"versionCreatedAt":"2024-12-19 12:53:45","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5470638","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5470638","identity":"rs-5470638","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}