Associations Between Pain and Cognitive Impairment in Older Adults: Findings from the Birjand Longitudinal Aging Study

Associations Between Pain and Cognitive Impairment in Older Adults: Findings from the Birjand Longitudinal Aging 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 Associations Between Pain and Cognitive Impairment in Older Adults: Findings from the Birjand Longitudinal Aging Study Akam Ramezani, Shakiba Rahimi, Azin Soltani, Hossein Fakhrzadeh, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8852522/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 12 You are reading this latest preprint version Abstract Background : Chronic pain is highly prevalent among older adults and has been shown to be associated with differences in cognitive function. While pain intensity reflects the severity of pain, pain interference assesses the extent to which pain disrupts daily activities. Distinguishing between these dimensions of pain and their associations with cognitive function may improve understanding of how pain relates to cognitive health in older populations. Methods : This cross-sectional study was conducted on baseline data from the Birjand Longitudinal Aging Study (BLAS). Pain was assessed using the Brief Pain Inventory (BPI), with average pain intensity measured by the BPI-5 score and pain interference by the BPI-9 score. Cognitive impairment was determined based on the combination results of the Six Item Cognitive Impairment Test (6-CIT), the Abbreviated Mental Test Score (AMTS), and the Category Fluency Test (CFT). Multiple logistic regression models were employed to examine associations between pain measures and cognitive impairment, adjusting for potential confounders. Results : Among 1,343 participants (mean age: 69.73 ± 7.53 years; 51.82% female), 59.64% were classified as cognitively impaired. In multivariable logistic regression analyses, higher pain interference (BPI-9) was significantly associated with cognitive impairment (OR = 1.01, 95% CI: 1.00–1.03, p = 0.002). Whereas, pain intensity (BPI-5) showed no significant association with cognitive impairment (OR = 1.00, 95% CI: 0.94–1.06, p = 0.019). Conclusion : This study underscores the significant association between pain interference and cognitive impairment in older adults. These findings highlight the importance of addressing pain's impact on daily functioning to mitigate cognitive decline in this population. Chronic pain pain interference cognitive impairment older adults Birjand Longitudinal Aging Study Introduction Cognitive impairment refers to a decline in one or more cognitive functions across various domains, such as executive functioning, memory, attention, numerical skills, language, literacy, and orientation. It is categorized into two main types: mild cognitive impairment and dementia (1). Approximately 55 million individuals globally are affected by dementia, with a higher concentration in low- and middle-income countries (2). According to a recent systematic review, the prevalence of dementia in Iran exhibits significant geographical variation, ranging from 0.02% to 0.43% (3). Also in terms of economic impact, it is estimated that $ 810,391,868 is expended annually on Alzheimer's disease (4). Current medications for Alzheimer's disease show limited efficacy in altering cognitive decline (5). As a result, action should be taken to slow disease progression. Low physical activity, hypertension, obesity, and depression are some known risk factors of cognitive impairment (6). Some studies also have shown the relationship between pain and cognitive decline (7, 8). The increasing prevalence of both chronic and acute diseases due to aging has increased the likelihood of experiencing pain in older adults (9). Moreover, in developing countries, people who suffer from pain do not have proper access to treatment (10). According to the results of two cohort studies, chronic pain measured at the baseline was found to predict memory decline and/or an increased risk of dementia after four (11) or twelve years follow-up (8). A recent cohort study that assessed both pain interference with daily activities and pain intensity in relation to cognitive impairment, demonstrated that only pain interference was found to increase the risk of cognitive decline (7). On the other hand, a meta-analysis that included ten longitudinal cohort studies showed that chronic pain cannot result in cognitive impairment (12). There are several potential pathways in which pain may contribute to cognitive decline. The most common explanation is the competition hypothesis. Pain occupies brain areas that are responsible for cognition (13, 14). Also, in individuals with chronic pain, the gray matter of cortical regions, including the frontal cortex, has structural changes (15). In addition, there are some other mechanisms, such as neuroinflammation (16, 17) and existing psychosocial variables including depression and sleep deprivation (6, 18) in painful conditions that mediate cognitive decline. The complex interplay between chronic pain and cognitive decline underscores the need for further investigation. Understanding the association between pain and cognitive function provides critical insights and paves the way for more holistic approaches to treatment. Due to the high burden of cognitive impairment on health systems and poor pain management in developing countries, we aimed to study, the relationship between pain and cognitive impairment in a large community-based sample of elderly individuals in Iran. Methods Study design and population This study is based on a cross-sectional analysis of the baseline data collected from the Birjand Longitudinal Aging Study (BLAS), which took place from September 2018 to April 2019. The BLAS is an ongoing research project that focuses on individuals aged 60 and older living in both urban and rural areas of Birjand County, located in the eastern part of Iran. For the urban part of the study, researchers identified 70 clusters based on postal codes, selecting 20 individuals from each cluster (19). In the rural areas, participants were recruited from ten health centers across Birjand County, using both digital and paper-based records. To be included in the study, participants had to be 60 years or older and able to participate actively. We excluded those who were bedridden, or suffered from conditions like Alzheimer’s disease that made communication difficult, as well as those with a life expectancy of less than six months. For the current study, data from 1343 participants were utilized out of the 1420 individuals from the initial wave of the BLAS cohort. The data collection process involved eight teams of trained interviewers, each responsible for gathering different types of information. Data was recorded using the Digit software, which helped validate the information in real-time and minimized missing data. All the collected data was securely stored on a remote server at the Endocrinology and Metabolism Research Institute in Tehran. We used detailed, validated questionnaires to collect a wide range of information, including sociodemographic details such as age, gender, education, occupation, marital status, income, smoking habits, physical activity, and health. Participants were also asked about their physical and mental health, pain levels, and any chronic conditions they had, including hypertension, diabetes, heart disease, Alzheimer’s, Parkinson’s, and many others. More information on the study design and methods can be found in previously published study protocol (19). Cognitive status assessment Cognitive function was assessed using three different evaluation tools. These included the Six Item Cognitive Impairment Test (6-CIT), the Abbreviated Mental Test Score (AMTS), and the Category Fluency Test (CFT), which specifically focused on animal naming. The 6-CIT is a relatively new tool that includes six items designed to assess orientation, memory, and attention. The participants who scored between 0 and 7 were considered to have normal cognitive function, while those scoring 8 or higher were classified as having cognitive impairment, which may indicate dementia (20). The AMTS, which is available in Persian, consists of 10 questions that evaluate both short-term and long-term memory, as well as orientation and attention. Previous studies in Iran have validated the psychometric properties of this scale (21). Finally, the Category Fluency Test (CFT), which assesses semantic memory and language abilities, asked participants to name as many animals as possible in 60 seconds. This test is commonly used to evaluate how well individuals can access stored knowledge and produce words under time constraints (22). Pain assessment Pain was assessed using the Brief Pain Inventory (BPI), a validated 9-item self-reported questionnaire designed to measure pain severity and its interference with daily functioning. In this study, pain intensity was assessed using the BPI-5 score, which represents average pain intensity rated on a 10-point Likert scale ranging from 0 (“no pain”) to 10 (“the worst pain imaginable”). Pain interference was evaluated using the BPI-9 score, comprising seven items that assess the extent to which pain interferes with general activity, walking ability, work, mood, enjoyment of life, social relationships, and sleep. Each item was rated on a 10-point Likert scale from 0 (“does not interfere”) to 10 (“completely interferes”), and a composite pain interference score was calculated as the mean of these items. The psychometric properties of the BPI have been previously validated in the Iranian population (23). Other variables The Mini Nutritional Assessment (MNA) was employed to assess the nutritional status of the participants. This standardized 18-item questionnaire encompasses various domains, including anthropometric measurements, dietary habits, and global health assessments, with a total possible score of 30. Based on their scores, participants were categorized into three groups: malnourished (score ≤ 16.5), at risk of malnutrition (score between 17 and 23.5), and well-nourished (score > 23.5). The MNA is among the most widely utilized nutritional screening tools for older adults in Iran and has been validated for this population (24, 25). The Patient Health Questionnaire-9 (PHQ-9) was utilized to assess the presence and severity of depression. As a component of the PRIME-MD diagnostic tool, the PHQ-9 is recommended for the evaluation, screening, and diagnosis of mood disorders, particularly in older adults. This instrument has been validated for use within the Iranian population (26, 27). Additionally, the duration, pattern, and quality of sleep were assessed using seven targeted items derived from the Pittsburgh Sleep Quality Index (PSQI) (28). Moreover, this study assessed a range of covariates, including socio-demographic characteristics, health behaviors, anthropometric measurements, and health status indicators. Socio-demographic variables included age (years), sex (male or female), educational attainment (illiterate, school, diploma, or university), marital status (married or unmarried/widowed/divorced), living arrangement (living alone or with others), wealth quintile (second to fifth), and employment status (retired/unemployed, housewife, or employed). Health behavior variables included cigarette smoking (yes/no) and physical activity level (inactive/active). Anthropometric measurements included body mass index (BMI), calculated as weight in kilograms divided by height in meters squared (kg/m²). Health status indicators encompassed the presence of underlying chronic diseases and current medication use, as self-reported by participants. Statistical analysis Categorical variables were presented as frequencies and percentages, while continuous variables were summarized using descriptive statistics, including means and standard deviations. A two-sample t-test was applied to examine the relationship between cognitive status and quantitative variables. For categorical variables, either Fisher's exact test or the chi-square test was used to evaluate group differences. Participants were divided into two groups for the analysis: those classified as cognitively normal based on the results of three cognitive assessments were categorized as having normal cognition, while the remaining participants were categorized as cognitively impaired. In addition, a sensitivity analysis was conducted comparing participants who demonstrated normal performance on all three cognitive tests with those who showed impairment on all three tests, in order to assess the robustness of the findings. Univariate and multivariable binary logistic regression models were used to examine the association between pain scores and cognitive impairment, with pain scores entered as continuous variables. A directed acyclic graph (DAG) was developed using DAGitty to represent assumed causal relationships between pain, cognitive impairment, and potential confounders; covariates included in the final regression models were selected based on the minimally sufficient adjustment set identified from this DAG (29). The results were presented as odds ratios (ORs) with 95% confidence intervals (CIs). Data analysis was conducted using STATA version 17.0 (StataCorp LLC, College Station, TX, USA). A p-value of ≤ 0.05 was considered statistically significant. Results The study included 1343 participants, with 696 (51.82%) females and 647 (48.18%) males. The mean age of the participants was 69.73 ± 7.53 years. Most participants were nonsmokers (91.36%) and approximately half were physically active (50.85%). Only 7.89% (n = 106) had attained a university-level education, and the majority were either housekeepers or retired (82.35%). Based on the combined results of the three cognitive assessments, 801 participants (59.64%) were classified as cognitively impaired, while 542 (40.36%) were classified as cognitively normal. As shown in Table 1 , cognitive impairment was significantly associated with older age, female sex, lower educational attainment, physical inactivity, living alone, poorer nutritional status, being a housekeeper, and the presence of depressive symptoms (all p < 0.01). In contrast, no significant differences were observed between cognitive status groups with respect to BMI, smoking status, multimorbidity, polypharmacy, or sleep quality. Table 1 Demographic and characteristics of participants according to their cognitive status Variables Normal cognitive Impaired cognitive P-Value Freq. Percent Freq. Percent sex female 210 38.75 486 60.67 < 0.01 male 332 61.25 315 39.33 age 60–69 362 66.79 391 48.81 < 0.01 70–79 151 27.86 270 33.71 ≥ 80 29 5.35 140 17.48 Educational level Illiterate 151 27.86 455 56.8 < 0.01 Primary school 175 32.29 248 30.96 High school 52 9.59 23 2.87 Diploma 93 17.16 40 4.99 Academic 71 13.1 35 4.37 BMI Low body weight 21 3.87 42 5.24 0.069 Ideal body weight 179 33.03 305 38.08 Over weight 227 41.88 284 35.46 Obese 115 21.22 170 21.22 Physical activity Inactive 221 40.85 438 54.68 < 0.01 Active 320 59.15 363 45.32 Smoking Yes 51 9.41 65 8.11 0.407 No 491 90.59 736 91.89 Living status Live with others 508 93.73 674 84.14 < 0.01 Live alone 34 6.27 127 15.86 MNA Malnourished 4 0.74 11 1.37 < 0.01 At risk 101 18.63 242 30.21 Well nourished 437 80.63 548 68.41 Morbidity number Less than 2 morbidities 296 57.59 414 54.55 0.284 ≥ 2 morbidities 218 42.41 345 45.45 Use more than 3 drugs Yes 75 13.84 132 16.48 0.188 No 467 86.16 669 83.52 Job status Retired 290 53.51 210 26.22 < 0.01 Employed 70 12.92 100 12.48 Housekeeper 153 28.23 453 56.55 Unemployed 29 5.35 38 4.47 PHQ9 Depressed mood 54 10.04 213 26.59 < 0.01 No depressed mood 484 89.96 588 73.41 Sleep quality Very good 49 9.04 52 6.49 0.249 Relatively good 359 66.24 562 70.16 Relatively bad 121 22.32 165 20.6 Vary bad 13 2.4 22 2.75 Associations between pain measures and cognitive impairment are presented in Table 2 . In crude analyses, both pain intensity (BPI-5) and pain interference (BPI-9) were significantly associated with cognitive impairment (BPI-5: OR = 1.03, 95% CI: 1.08–1.18, p < 0.001; BPI-9: OR = 1.03, 95% CI: 1.02–1.04, p < 0.001). After adjustment for age and sex (Model 1), these associations remained statistically significant (BPI-5: OR = 1.07, 95% CI: 1.01–1.12, p = 0.008; BPI-9: OR = 1.02, 95% CI: 1.01–1.03, p < 0.001). Table 2 Association between pain intensity and cognitive impairment: Results from logistic regression models Models BPI5 BPI9 OR (95% CI) p-value OR (95% CI) p-value Crude 1.03 (1.08–1.18) 0.000 1.03 (1.02–1.04) 0.000 Model 1 1.07 (1.01–1.12) 0.008 1.02 (1.01–1.03) 0.000 Model 2 1.06 (1.01–1.12) 0.019 1.01 (1.00-1.03) 0.002 Model 3 1.00 (0.94–1.06) 0.816 1.01 (1.00-1.02) 0.038 Model 1 adjusted for age, sex Model 2 adjusted for age, BMI, MNA, multimorbidity, smoking, physical activity, sleep quality, PHQ9 Model 3 adjusted for Sex, age, education year, wealth quintile, living arrangement, BMI, MNA, multimorbidity, polypharmacy, physical activity, current smoking, job, sleep quality, PHQ9 In the final model, following further adjustment for a comprehensive set of covariates, including age, BMI, MNA, multimorbidity, smoking, physical activity, sleep quality, and PHQ9 (Model 2), the association between pain intensity and cognitive impairment was still statistically significant (OR = 1.06, 95% CI: 1.01–1.12, p = 0.019), and this association was no longer significant in the fully adjusted model (Model 3: OR = 1.00, 95% CI: 0.94–1.06, p = 0.816). In contrast, pain interference remained significantly associated with cognitive impairment in the final model (OR = 1.01, 95% CI: 1.00–1.03, p = 0.002) and fully adjusted model (Model 3: OR = 1.01, 95% CI: 1.00–1.02, p = 0.038). Sensitivity analyses employing different pain intensity measures yielded broadly similar patterns to the main analyses, with significant associations observed in crude and minimally adjusted models that were attenuated and no longer statistically significant in fully adjusted models (Table 3 ). Table 3 Sensitivity analysis of the association between pain intensity and cognitive impairment using different pain scales Models BPI5 BPI9 OR (95% CI) p -value OR (95% CI) p -value Crude 1.15 (1.09–1.21) < 0.001 1.03 (1.03–1.04) < 0.001 Model 1 1.04 (0.98–1.10) 0.171 1.02 (1.01–1.03) 0.001 Model 2 1.05 (0.99–1.12) 0.062 1.02 (1.01–1.03) 0.005 Model 3 0.97 (0.90–1.04) 0.350 1.01 (1.00–1.02) 0.220 Model 1 adjusted for age, sex Model 2 adjusted for age, BMI, MNA, multimorbidity, smoking, physical activity, sleep quality, PHQ9 Model 3 adjusted for Sex, age, education year, wealth quintile, living arrangement, BMI, MNA, multimorbidity, polypharmacy, physical activity, current smoking, job, sleep quality, PHQ9 Supplementary Table S1. Univariate logistic regression analysis of factors associated with cognitive impairment Univariate analyses examining associations between socio-demographic and health-related variables and cognitive impairment are presented in Supplementary Table S1. In brief, older age, lower educational attainment, physical inactivity, poorer nutritional status, living alone, and employment as a housekeeper were associated with higher odds of cognitive impairment, whereas higher wealth status and physical activity were associated with lower odds. No significant associations were observed for body mass index, smoking status, multimorbidity, or polypharmacy. Discussion In our study, we found that both pain intensity and pain interference were associated with greater odds of cognitive impairment after adjusting for health and lifestyle factors including BMI, nutritional status, multimorbidity, smoking, physical activity, sleep quality, and depressive symptoms .However, in the fully adjusted model which additionally accounted for education, wealth, living arrangement, polypharmacy, and employment, the association between pain intensity and cognitive impairment was no longer significant (OR = 1.00, p = 0.816), whereas pain interference remained significantly associated (OR = 1.01, p = 0.038). These findings corroborate previous research showing a positive association between pain interference and cognitive impairment (7, 30–36). Prior cross-sectional studies have frequently reported poorer cognitive performance among individuals with chronic pain, particularly in domains such as attention, memory, executive function, and processing speed (37–39). However, other studies have found no significant associations between pain severity or interference and cognitive dysfunction, highlighting heterogeneity in findings (40, 41). Longitudinal evidence has also been mixed. While one prospective study showed accelerated 10-year cognitive decline associated with persistent pain (8), and another found a correlation between pain intensity and cognitive decline over 2.75 years (42), two longitudinal studies discovered that, pain interference, but not pain intensity, was linked to the cognitive dysfunction (7, 43). Long-term cohort studies have further suggested that chronic pain may be associated with accelerated decline in specific cognitive domains, such as processing speed, independent of depression, medication use, and comorbidities (44, 45). In contrast, some longitudinal analyses have failed to demonstrate a significant association after accounting for confounding factors (46). Meta-analytic evidence has similarly been inconsistent, with one meta-analysis reporting an overall association between pain and cognitive dysfunction (47), while another focusing on longitudinal cohorts found no clear association between chronic pain and incident cognitive impairment (12). Several biological and psychological mechanisms may explain the observed association between pain interference and cognitive impairment. Chronic pain involves sustained engagement of central neural networks implicated in both nociception and cognition, although the precise mechanisms remain incompletely understood (48, 49). Neuroimaging studies have demonstrated that chronic pain is associated with structural and functional alterations in limbic regions, including the hippocampus, amygdala, and cingulate cortex, which play key roles in memory, learning, emotional regulation, and attention (50–52). Individuals with chronic pain also exhibit a reduction in the volume of the thalamus, insular cortex, and cingulate cortex, which are part of the limbic-related cortex and are involved in executive functions, language, memory, and attention (53, 54). Apkarian et al. demonstrated prefrontal cortex involvement in chronic pain (55). This brain region is essential for higher-level cognitive functions including action planning and execution, goal-directed behavior, and inhibitory control (56, 57). Moreover, alterations in brain structure and connectivity have been linked to maladaptive cognitive processes such as pain catastrophizing, characterized by heightened attention to pain-related stimuli and difficulty disengaging from perceived threats (58–61). These cognitive-emotional processes may increase cognitive load and limit available cognitive resources, thereby contributing to poorer cognitive performance. Systemic inflammation may represent an additional pathway linking pain and cognitive impairment. Chronic pain has been associated with elevated inflammatory markers, including C-reactive protein (CRP) (45), and inflammation has been implicated in cognitive decline and neurodegenerative processes, including Alzheimer’s disease (62). Although inflammatory biomarkers were not directly assessed in the present study, this pathway warrants further investigation in future research. The differential associations observed for pain intensity and pain interference may reflect their distinct conceptual meanings. Pain intensity reflects the subjective experience of how severe the pain feels, whereas pain interference measures how much pain affects daily activities and overall quality of life. The differences in their association with cognitive decline may be due to this distinction between the two aspects of pain (63). One possible explanation is that pain interference. encompassing the broader impact of pain on an individual's functional and emotional well-being, likely consumes more cognitive resources than pain that doesn't interfere with daily activities (43, 64). The relationship between pain and cognitive function is likely bidirectional. Previous studies have found that higher baseline cognitive performance is associated with lower pain intensity and less interference from pain at follow-up (65, 66). Previous findings strongly support the significant roles of cognitive and emotional factors in the development of chronic pain (67, 68). Cognitive dysfunction in individuals with chronic pain has been shown to be more strongly related to psychological distress and negative affect than to pain intensity itself (69, 70). However, in our study even after adjusting for PHQ-9, pain interference was still associated with cognitive dysfunction. Consistent with prior research, higher levels of depressive symptoms were associated with greater pain interference (71–73). From a clinical and public health perspective, these findings highlight the importance of assessing pain interference, rather than pain intensity alone, in older adults. Future research should concentrate on the impact of non-pharmacological treatments on the connection between pain and cognitive impairment. By focusing on these strategies, healthcare systems can improve patient outcomes and guide policy decisions on pain management, ultimately enhancing the quality of life for individuals dealing with chronic pain and cognitive decline. This study has several limitations that should be acknowledged. First, the observational nature of the data precludes establishing causal relationships between chronic pain and cognitive decline. Second, reliance on self-reported questionnaires to assess pain may introduce recall bias, particularly among older adults who may have impaired memory. Additionally, the study did not account for specific types of pain (e.g., neuropathic, inflammatory), the duration of pain, or the use of pain medications, all of which could influence cognitive outcomes. The absence of these variables limits the granularity of our findings. Future research should utilize prospective longitudinal studies with well-defined pain classifications and thorough cognitive evaluations, while accounting for potential confounders, to better understand the temporal relationships and causal mechanisms connecting chronic pain to cognitive decline and dementia. Despite these limitations, the study has several important strengths. The large sample size and population-based design of the Birjand Longitudinal Aging Study enhance the statistical power and generalizability of the findings to community-dwelling older adults. Cognitive function was assessed using multiple validated screening instruments, capturing complementary cognitive domains and reducing the likelihood of outcome misclassification based on a single test. In addition, adjustment for a wide range of potential confounders strengthens the robustness of the observed association between pain interference and cognitive impairment. These strengths support the validity of the findings and highlight the importance of distinguishing pain interference from pain intensity in studies of cognitive health in older adults. Future longitudinal studies with detailed pain phenotyping and comprehensive cognitive assessment are warranted to clarify causal pathways linking pain to cognitive decline. Conclusion In this population-based study of older adults, pain interference was independently associated with cognitive impairment, whereas pain intensity was not. These findings suggest that the functional impact of pain on daily life may be more relevant to cognitive health than perceived pain severity alone. Differentiating pain dimensions may therefore help identify older individuals at higher risk of cognitive impairment. Clinically, routine assessment of pain interference and interventions targeting pain-related functional limitations may represent modifiable strategies to support cognitive health in aging populations. Future longitudinal studies with detailed pain characterization are needed to clarify causal pathways and underlying mechanisms. Declarations Ethics approval and consent to participate : This study, part of the Birjand Longitudinal Aging Study (BLAS) in Birjand, Iran, received ethical approval from the Birjand University of Medical Sciences (IR.BUMS.Rec.1397.282) and Tehran University of Medical Sciences' Endocrine and Metabolism Research Institute (IR.TUMS.EMRI.REC.1396.00158). All procedures followed the Declaration of Helsinki. Informed consent was obtained from all participants; for those with cognitive impairment (Abbreviated Mental Test Score < 7), consent was obtained from a close relative or legal guardian. Illiterate participants provided consent via fingerprint after the form was read aloud by a trusted individual. Consent for publication : Not applicable Availability of data and materials : The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. Clinical trial number :not applicable Competing interests : The authors declare that they have no competing interests Funding : There is no specific funding received for this study Authors contributions : HE, FS, MM and HF designed and interpreted the result. AR,SR and AS wrote the manuscript which was edited by HE and FS.AR analyzed the results References Petersen RC, Lopez O, Armstrong MJ, Getchius TSD, Ganguli M, Gloss D, et al. Practice guideline update summary: Mild cognitive impairment: Report of the Guideline Development, Dissemination, and Implementation Subcommittee of the American Academy of Neurology. Neurology. 2018;90(3):126-35. World Health Organization. Dementia (2021) [Available from: https://www.who.int/news-room/fact-sheets/detail/dementia. 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Schepker CA, Leveille SG, Pedersen MM, Ward RE, Kurlinski LA, Grande L, et al. Effect of Pain and Mild Cognitive Impairment on Mobility. Journal of the American Geriatrics Society. 2016;64(1):138-43. Lopes MA, Xavier AJ, D'Orsi E. Cognitive and functional impairment in an older community population from Brazil: The intriguing association with frequent pain. Archives of gerontology and geriatrics. 2016;66:134-9. Scemes E, Zammit AR, Katz MJ, Lipton RB, Derby CA. Associations of cognitive function and pain in older adults. International journal of geriatric psychiatry. 2017;32(1):118-20. van der Leeuw G, Eggermont LH, Shi L, Milberg WP, Gross AL, Hausdorff JM, et al. Pain and Cognitive Function Among Older Adults Living in the Community. The journals of gerontology Series A, Biological sciences and medical sciences. 2016;71(3):398-405. Ikram M, Innes K, Sambamoorthi U. Association of osteoarthritis and pain with Alzheimer's Diseases and Related Dementias among older adults in the United States. Osteoarthritis and cartilage. 2019;27(10):1470-80. Higgins DM, Martin AM, Baker DG, Vasterling JJ, Risbrough V. The Relationship Between Chronic Pain and Neurocognitive Function: A Systematic Review. Clin J Pain. 2018;34(3):262-75. Borges MK, Canevelli M, Cesari M, Aprahamian I. Frailty as a Predictor of Cognitive Disorders: A Systematic Review and Meta-Analysis. Frontiers in medicine. 2019;6:26. Oosterman J, Derksen LC, van Wijck AJ, Kessels RP, Veldhuijzen DS. Executive and attentional functions in chronic pain: does performance decrease with increasing task load? Pain research & management. 2012;17(3):159-65. Terassi M, Rossetti ES, Gramani-Say K, Alexandre TDS, Hortense P, Pavarini SCI. Comparison of the cognitive performance of elderly caregivers with and without chronic pain. Revista da Escola de Enfermagem da U S P. 2017;51:e03260. van der Leeuw G, Ayers E, Leveille SG, Blankenstein AH, van der Horst HE, Verghese J. The Effect of Pain on Major Cognitive Impairment in Older Adults. The Journal of Pain. 2018;19(12):1435-44. van der Leeuw G, Ayers E, Leveille SG, Blankenstein AH, van der Horst HE, Verghese J. The Effect of Pain on Major Cognitive Impairment in Older Adults. J Pain. 2018;19(12):1435-44. Ezzati A, Wang C, Katz MJ, Derby CA, Zammit AR, Zimmerman ME, et al. The Temporal Relationship between Pain Intensity and Pain Interference and Incident Dementia. Current Alzheimer research. 2019;16(2):109-15. Rouch I, Edjolo A, Laurent B, Pongan E, Dartigues J-F, Amieva H. Association between chronic pain and long-term cognitive decline in a population-based cohort of elderly participants. PAIN. 2021;162(2):552-60. Rong W, Zhang C, Zheng F, Xiao S, Yang Z, Xie W. Persistent moderate to severe pain and long-term cognitive decline. European journal of pain (London, England). 2021;25(9):2065-74. Veronese N, Koyanagi A, Solmi M, Thompson T, Maggi S, Schofield P, et al. Pain is not associated with cognitive decline in older adults: A four-year longitudinal study. Maturitas. 2018;115:92-6. Zhang X, Gao R, Zhang C, Chen H, Wang R, Zhao Q, et al. Evidence for Cognitive Decline in Chronic Pain: A Systematic Review and Meta-Analysis. Frontiers in neuroscience. 2021;15:737874. Ferreira Kdos S, Oliver GZ, Thomaz DC, Teixeira CT, Foss MP. Cognitive deficits in chronic pain patients, in a brief screening test, are independent of comorbidities and medication use. Arquivos de neuro-psiquiatria. 2016;74(5):361-6. Schiltenwolf M, Akbar M, Hug A, Pfüller U, Gantz S, Neubauer E, et al. Evidence of specific cognitive deficits in patients with chronic low back pain under long-term substitution treatment of opioids. Pain physician. 2014;17(1):9-20. McCarberg B, Peppin J. Pain Pathways and Nervous System Plasticity: Learning and Memory in Pain. Pain medicine (Malden, Mass). 2019;20(12):2421-37. Gogolla N. The insular cortex. Current biology : CB. 2017;27(12):R580-r6. Marchand S. The physiology of pain mechanisms: from the periphery to the brain. Rheumatic diseases clinics of North America. 2008;34(2):285-309. Morlion B, Coluzzi F, Aldington D, Kocot-Kepska M, Pergolizzi J, Mangas AC, et al. Pain chronification: what should a non-pain medicine specialist know? Current medical research and opinion. 2018;34(7):1169-78. Wolff M, Vann SD. The Cognitive Thalamus as a Gateway to Mental Representations. The Journal of neuroscience : the official journal of the Society for Neuroscience. 2019;39(1):3-14. Apkarian AV, Thomas PS, Krauss BR, Szeverenyi NM. Prefrontal cortical hyperactivity in patients with sympathetically mediated chronic pain. Neuroscience letters. 2001;311(3):193-7. Miller EK. The prefrontal cortex and cognitive control. Nature reviews Neuroscience. 2000;1(1):59-65. Munakata Y, Herd SA, Chatham CH, Depue BE, Banich MT, O'Reilly RC. A unified framework for inhibitory control. Trends in cognitive sciences. 2011;15(10):453-9. Blankstein U, Chen J, Diamant NE, Davis KD. Altered brain structure in irritable bowel syndrome: potential contributions of pre-existing and disease-driven factors. Gastroenterology. 2010;138(5):1783-9. Burgmer M, Petzke F, Giesecke T, Gaubitz M, Heuft G, Pfleiderer B. Cerebral activation and catastrophizing during pain anticipation in patients with fibromyalgia. Psychosomatic medicine. 2011;73(9):751-9. Loggia ML, Berna C, Kim J, Cahalan CM, Martel MO, Gollub RL, et al. The lateral prefrontal cortex mediates the hyperalgesic effects of negative cognitions in chronic pain patients. J Pain. 2015;16(8):692-9. Crombez G, Eccleston C, Baeyens F, Eelen P. When somatic information threatens, catastrophic thinking enhances attentional interference. Pain. 1998;75(2-3):187-98. Zheng F, Xie W. High-sensitivity C-reactive protein and cognitive decline: the English Longitudinal Study of Ageing. Psychological medicine. 2018;48(8):1381-9. Tan G, Jensen MP, Thornby JI, Shanti BF. Validation of the Brief Pain Inventory for chronic nonmalignant pain. J Pain. 2004;5(2):133-7. Li G, He Z, Hu J, Xiao C, Fan W, Zhang Z, et al. Association between pain interference and motoric cognitive risk syndrome in older adults: a population-based cohort study. BMC geriatrics. 2024;24(1):437. Milani SA, Bell Tyler R, Crowe M, Pope Caitlin N, Downer B. Increasing Pain Interference Is Associated With Cognitive Decline Over Four Years Among Older Puerto Rican Adults. The Journals of Gerontology: Series A. 2022;78(6):1005-12. James RJE, Ferguson E. The dynamic relationship between pain, depression and cognitive function in a sample of newly diagnosed arthritic adults: a cross-lagged panel model. Psychological medicine. 2019;50(10):1663-71. Wiech K, Ploner M, Tracey I. Neurocognitive aspects of pain perception. Trends in cognitive sciences. 2008;12(8):306-13. Apkarian AV, Bushnell MC, Treede R-D, Zubieta J-K. Human brain mechanisms of pain perception and regulation in health and disease. European Journal of Pain. 2005;9(4):463-. Kewman DG, Vaishampayan N, Zald D, Han B. Cognitive impairment in musculoskeletal pain patients. International journal of psychiatry in medicine. 1991;21(3):253-62. Grace GM, Nielson WR, Hopkins M, Berg MA. Concentration and memory deficits in patients with fibromyalgia syndrome. Journal of clinical and experimental neuropsychology. 1999;21(4):477-87. Bell TR, Sprague BN, Ross LA. Longitudinal associations of pain and cognitive decline in community-dwelling older adults. Psychology and aging. 2022;37(6):715-30. Milani SA, Sanchez C, Kuo YF, Downer B, Al Snih S, Markides KS, et al. Pain and incident cognitive impairment in very old Mexican American adults. Journal of the American Geriatrics Society. 2024;72(1):226-35. Magni G, Moreschi C, Rigatti-Luchini S, Merskey H. Prospective study on the relationship between depressive symptoms and chronic musculoskeletal pain. Pain. 1994;56(3):289-97. Additional Declarations No competing interests reported. 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It is categorized into two main types: mild cognitive impairment and dementia (1). Approximately 55\u0026nbsp;million individuals globally are affected by dementia, with a higher concentration in low- and middle-income countries (2). According to a recent systematic review, the prevalence of dementia in Iran exhibits significant geographical variation, ranging from 0.02% to 0.43% (3). Also in terms of economic impact, it is estimated that \u003cspan\u003e$\u003c/span\u003e810,391,868 is expended annually on Alzheimer's disease (4). Current medications for Alzheimer's disease show limited efficacy in altering cognitive decline (5). As a result, action should be taken to slow disease progression. Low physical activity, hypertension, obesity, and depression are some known risk factors of cognitive impairment (6). Some studies also have shown the relationship between pain and cognitive decline (7, 8). The increasing prevalence of both chronic and acute diseases due to aging has increased the likelihood of experiencing pain in older adults (9). Moreover, in developing countries, people who suffer from pain do not have proper access to treatment (10).\u003c/p\u003e \u003cp\u003eAccording to the results of two cohort studies, chronic pain measured at the baseline was found to predict memory decline and/or an increased risk of dementia after four (11) or twelve years follow-up (8). A recent cohort study that assessed both pain interference with daily activities and pain intensity in relation to cognitive impairment, demonstrated that only pain interference was found to increase the risk of cognitive decline (7). On the other hand, a meta-analysis that included ten longitudinal cohort studies showed that chronic pain cannot result in cognitive impairment (12).\u003c/p\u003e \u003cp\u003eThere are several potential pathways in which pain may contribute to cognitive decline. The most common explanation is the competition hypothesis. Pain occupies brain areas that are responsible for cognition (13, 14). Also, in individuals with chronic pain, the gray matter of cortical regions, including the frontal cortex, has structural changes (15). In addition, there are some other mechanisms, such as neuroinflammation (16, 17) and existing psychosocial variables including depression and sleep deprivation (6, 18) in painful conditions that mediate cognitive decline.\u003c/p\u003e \u003cp\u003eThe complex interplay between chronic pain and cognitive decline underscores the need for further investigation. Understanding the association between pain and cognitive function provides critical insights and paves the way for more holistic approaches to treatment. Due to the high burden of cognitive impairment on health systems and poor pain management in developing countries, we aimed to study, the relationship between pain and cognitive impairment in a large community-based sample of elderly individuals in Iran.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and population\u003c/h2\u003e \u003cp\u003eThis study is based on a cross-sectional analysis of the baseline data collected from the Birjand Longitudinal Aging Study (BLAS), which took place from September 2018 to April 2019. The BLAS is an ongoing research project that focuses on individuals aged 60 and older living in both urban and rural areas of Birjand County, located in the eastern part of Iran. For the urban part of the study, researchers identified 70 clusters based on postal codes, selecting 20 individuals from each cluster (19). In the rural areas, participants were recruited from ten health centers across Birjand County, using both digital and paper-based records. To be included in the study, participants had to be 60 years or older and able to participate actively. We excluded those who were bedridden, or suffered from conditions like Alzheimer\u0026rsquo;s disease that made communication difficult, as well as those with a life expectancy of less than six months. For the current study, data from 1343 participants were utilized out of the 1420 individuals from the initial wave of the BLAS cohort. The data collection process involved eight teams of trained interviewers, each responsible for gathering different types of information. Data was recorded using the Digit software, which helped validate the information in real-time and minimized missing data. All the collected data was securely stored on a remote server at the Endocrinology and Metabolism Research Institute in Tehran.\u003c/p\u003e \u003cp\u003eWe used detailed, validated questionnaires to collect a wide range of information, including sociodemographic details such as age, gender, education, occupation, marital status, income, smoking habits, physical activity, and health. Participants were also asked about their physical and mental health, pain levels, and any chronic conditions they had, including hypertension, diabetes, heart disease, Alzheimer\u0026rsquo;s, Parkinson\u0026rsquo;s, and many others. More information on the study design and methods can be found in previously published study protocol (19).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eCognitive status assessment\u003c/h3\u003e\n\u003cp\u003eCognitive function was assessed using three different evaluation tools. These included the Six Item Cognitive Impairment Test (6-CIT), the Abbreviated Mental Test Score (AMTS), and the Category Fluency Test (CFT), which specifically focused on animal naming. The 6-CIT is a relatively new tool that includes six items designed to assess orientation, memory, and attention. The participants who scored between 0 and 7 were considered to have normal cognitive function, while those scoring 8 or higher were classified as having cognitive impairment, which may indicate dementia (20). The AMTS, which is available in Persian, consists of 10 questions that evaluate both short-term and long-term memory, as well as orientation and attention. Previous studies in Iran have validated the psychometric properties of this scale (21). Finally, the Category Fluency Test (CFT), which assesses semantic memory and language abilities, asked participants to name as many animals as possible in 60 seconds. This test is commonly used to evaluate how well individuals can access stored knowledge and produce words under time constraints (22).\u003c/p\u003e\n\u003ch3\u003ePain assessment\u003c/h3\u003e\n\u003cp\u003ePain was assessed using the Brief Pain Inventory (BPI), a validated 9-item self-reported questionnaire designed to measure pain severity and its interference with daily functioning. In this study, pain intensity was assessed using the BPI-5 score, which represents average pain intensity rated on a 10-point Likert scale ranging from 0 (\u0026ldquo;no pain\u0026rdquo;) to 10 (\u0026ldquo;the worst pain imaginable\u0026rdquo;). Pain interference was evaluated using the BPI-9 score, comprising seven items that assess the extent to which pain interferes with general activity, walking ability, work, mood, enjoyment of life, social relationships, and sleep. Each item was rated on a 10-point Likert scale from 0 (\u0026ldquo;does not interfere\u0026rdquo;) to 10 (\u0026ldquo;completely interferes\u0026rdquo;), and a composite pain interference score was calculated as the mean of these items. The psychometric properties of the BPI have been previously validated in the Iranian population (23).\u003c/p\u003e\n\u003ch3\u003eOther variables\u003c/h3\u003e\n\u003cp\u003eThe Mini Nutritional Assessment (MNA) was employed to assess the nutritional status of the participants. This standardized 18-item questionnaire encompasses various domains, including anthropometric measurements, dietary habits, and global health assessments, with a total possible score of 30. Based on their scores, participants were categorized into three groups: malnourished (score\u0026thinsp;\u0026le;\u0026thinsp;16.5), at risk of malnutrition (score between 17 and 23.5), and well-nourished (score\u0026thinsp;\u0026gt;\u0026thinsp;23.5). The MNA is among the most widely utilized nutritional screening tools for older adults in Iran and has been validated for this population (24, 25). The Patient Health Questionnaire-9 (PHQ-9) was utilized to assess the presence and severity of depression. As a component of the PRIME-MD diagnostic tool, the PHQ-9 is recommended for the evaluation, screening, and diagnosis of mood disorders, particularly in older adults. This instrument has been validated for use within the Iranian population (26, 27). Additionally, the duration, pattern, and quality of sleep were assessed using seven targeted items derived from the Pittsburgh Sleep Quality Index (PSQI) (28). Moreover, this study assessed a range of covariates, including socio-demographic characteristics, health behaviors, anthropometric measurements, and health status indicators. Socio-demographic variables included age (years), sex (male or female), educational attainment (illiterate, school, diploma, or university), marital status (married or unmarried/widowed/divorced), living arrangement (living alone or with others), wealth quintile (second to fifth), and employment status (retired/unemployed, housewife, or employed). Health behavior variables included cigarette smoking (yes/no) and physical activity level (inactive/active). Anthropometric measurements included body mass index (BMI), calculated as weight in kilograms divided by height in meters squared (kg/m\u0026sup2;). Health status indicators encompassed the presence of underlying chronic diseases and current medication use, as self-reported by participants.\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eCategorical variables were presented as frequencies and percentages, while continuous variables were summarized using descriptive statistics, including means and standard deviations. A two-sample t-test was applied to examine the relationship between cognitive status and quantitative variables. For categorical variables, either Fisher's exact test or the chi-square test was used to evaluate group differences. Participants were divided into two groups for the analysis: those classified as cognitively normal based on the results of three cognitive assessments were categorized as having normal cognition, while the remaining participants were categorized as cognitively impaired. In addition, a sensitivity analysis was conducted comparing participants who demonstrated normal performance on all three cognitive tests with those who showed impairment on all three tests, in order to assess the robustness of the findings. Univariate and multivariable binary logistic regression models were used to examine the association between pain scores and cognitive impairment, with pain scores entered as continuous variables. A directed acyclic graph (DAG) was developed using DAGitty to represent assumed causal relationships between pain, cognitive impairment, and potential confounders; covariates included in the final regression models were selected based on the minimally sufficient adjustment set identified from this DAG (29). The results were presented as odds ratios (ORs) with 95% confidence intervals (CIs). Data analysis was conducted using STATA version 17.0 (StataCorp LLC, College Station, TX, USA). A p-value of \u0026le;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eThe study included 1343 participants, with 696 (51.82%) females and 647 (48.18%) males. The mean age of the participants was 69.73\u0026thinsp;\u0026plusmn;\u0026thinsp;7.53 years. Most participants were nonsmokers (91.36%) and approximately half were physically active (50.85%). Only 7.89% (n\u0026thinsp;=\u0026thinsp;106) had attained a university-level education, and the majority were either housekeepers or retired (82.35%). Based on the combined results of the three cognitive assessments, 801 participants (59.64%) were classified as cognitively impaired, while 542 (40.36%) were classified as cognitively normal.\u003c/p\u003e \u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, cognitive impairment was significantly associated with older age, female sex, lower educational attainment, physical inactivity, living alone, poorer nutritional status, being a housekeeper, and the presence of depressive symptoms (all p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). In contrast, no significant differences were observed between cognitive status groups with respect to BMI, smoking status, multimorbidity, polypharmacy, or sleep quality.\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\u003eDemographic and characteristics of participants according to their cognitive status\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=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eNormal cognitive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eImpaired cognitive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eP-Value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFreq.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePercent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eFreq.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePercent\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003esex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003efemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e210\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e486\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e60.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e332\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e61.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e315\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e39.33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60\u0026ndash;69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e362\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e66.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e391\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e48.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e70\u0026ndash;79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e151\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e270\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e33.71\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e140\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e17.48\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eEducational level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIlliterate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e151\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e455\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e56.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrimary school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e175\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e248\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e30.96\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.87\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDiploma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.99\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAcademic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.37\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow body weight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.069\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIdeal body weight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e179\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e305\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e38.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOver weight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e227\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e41.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e284\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e35.46\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eObese\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e170\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e21.22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePhysical activity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInactive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e221\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e40.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e438\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e54.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eActive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e320\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e59.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e363\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e45.32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSmoking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.407\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e491\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e90.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e736\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e91.89\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eLiving status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLive with others\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e508\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e93.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e674\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e84.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLive alone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e127\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15.86\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eMNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMalnourished\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAt risk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e242\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e30.21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWell nourished\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e437\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e80.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e548\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e68.41\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMorbidity number\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLess than 2 morbidities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e296\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e57.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e414\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e54.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.284\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;2 morbidities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e218\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e345\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e45.45\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eUse more than 3 drugs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e132\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e16.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.188\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e467\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e86.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e669\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e83.52\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eJob status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRetired\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e290\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e53.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e210\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e26.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEmployed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12.48\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHousekeeper\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e153\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e453\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e56.55\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnemployed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.47\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePHQ9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDepressed mood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e213\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e26.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo depressed mood\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e484\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e89.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e588\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e73.41\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eSleep quality\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVery good\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.249\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRelatively good\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e359\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e66.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e562\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e70.16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRelatively bad\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e121\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e165\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e20.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVary bad\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAssociations between pain measures and cognitive impairment are presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. In crude analyses, both pain intensity (BPI-5) and pain interference (BPI-9) were significantly associated with cognitive impairment (BPI-5: OR\u0026thinsp;=\u0026thinsp;1.03, 95% CI: 1.08\u0026ndash;1.18, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; BPI-9: OR\u0026thinsp;=\u0026thinsp;1.03, 95% CI: 1.02\u0026ndash;1.04, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). After adjustment for age and sex (Model 1), these associations remained statistically significant (BPI-5: OR\u0026thinsp;=\u0026thinsp;1.07, 95% CI: 1.01\u0026ndash;1.12, p\u0026thinsp;=\u0026thinsp;0.008; BPI-9: OR\u0026thinsp;=\u0026thinsp;1.02, 95% CI: 1.01\u0026ndash;1.03, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\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\u003eAssociation between pain intensity and cognitive impairment: Results from logistic regression models\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=\"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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eModels\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eBPI5\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eBPI9\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ep-value\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=\"c5\"\u003e \u003cp\u003ep-value\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\u003eCrude\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.03 (1.08\u0026ndash;1.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.03 (1.02\u0026ndash;1.04)\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\u003eModel 1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.07 (1.01\u0026ndash;1.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.02 (1.01\u0026ndash;1.03)\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\u003eModel 2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.06 (1.01\u0026ndash;1.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.01 (1.00-1.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.002\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\u003e1.00 (0.94\u0026ndash;1.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.816\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.01 (1.00-1.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.038\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eModel 1 adjusted for age, sex\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eModel 2 adjusted for age, BMI, MNA, multimorbidity, smoking, physical activity, sleep quality, PHQ9\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eModel 3 adjusted for Sex, age, education year, wealth quintile, living arrangement, BMI, MNA, multimorbidity, polypharmacy, physical activity, current smoking, job, sleep quality, PHQ9\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn the final model, following further adjustment for a comprehensive set of covariates, including age, BMI, MNA, multimorbidity, smoking, physical activity, sleep quality, and PHQ9 (Model 2), the association between pain intensity and cognitive impairment was still statistically significant (OR\u0026thinsp;=\u0026thinsp;1.06, 95% CI: 1.01\u0026ndash;1.12, p\u0026thinsp;=\u0026thinsp;0.019), and this association was no longer significant in the fully adjusted model (Model 3: OR\u0026thinsp;=\u0026thinsp;1.00, 95% CI: 0.94\u0026ndash;1.06, p\u0026thinsp;=\u0026thinsp;0.816). In contrast, pain interference remained significantly associated with cognitive impairment in the final model (OR\u0026thinsp;=\u0026thinsp;1.01, 95% CI: 1.00\u0026ndash;1.03, p\u0026thinsp;=\u0026thinsp;0.002) and fully adjusted model (Model 3: OR\u0026thinsp;=\u0026thinsp;1.01, 95% CI: 1.00\u0026ndash;1.02, p\u0026thinsp;=\u0026thinsp;0.038). Sensitivity analyses employing different pain intensity measures yielded broadly similar patterns to the main analyses, with significant associations observed in crude and minimally adjusted models that were attenuated and no longer statistically significant in fully adjusted models (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\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\u003eSensitivity analysis of the association between pain intensity and cognitive impairment using different pain scales\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=\"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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModels\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eBPI5\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eBPI9\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=\"c3\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\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=\"c5\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\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\u003eCrude\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.15 (1.09\u0026ndash;1.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.03 (1.03\u0026ndash;1.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\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\u003e1.04 (0.98\u0026ndash;1.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.171\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.02 (1.01\u0026ndash;1.03)\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\u003eModel 2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.05 (0.99\u0026ndash;1.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.062\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.02 (1.01\u0026ndash;1.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.005\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\u003e0.97 (0.90\u0026ndash;1.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.350\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.01 (1.00\u0026ndash;1.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.220\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eModel 1 adjusted for age, sex\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eModel 2 adjusted for age, BMI, MNA, multimorbidity, smoking, physical activity, sleep quality, PHQ9\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eModel 3 adjusted for Sex, age, education year, wealth quintile, living arrangement, BMI, MNA, multimorbidity, polypharmacy, physical activity, current smoking, job, sleep quality, PHQ9\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003cem\u003eSupplementary Table S1. Univariate logistic regression analysis of factors associated with cognitive impairment\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eUnivariate analyses examining associations between socio-demographic and health-related variables and cognitive impairment are presented in \u003cb\u003eSupplementary Table S1.\u003c/b\u003e In brief, older age, lower educational attainment, physical inactivity, poorer nutritional status, living alone, and employment as a housekeeper were associated with higher odds of cognitive impairment, whereas higher wealth status and physical activity were associated with lower odds. No significant associations were observed for body mass index, smoking status, multimorbidity, or polypharmacy.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn our study, we found that both pain intensity and pain interference were associated with greater odds of cognitive impairment after adjusting for health and lifestyle factors including BMI, nutritional status, multimorbidity, smoking, physical activity, sleep quality, and depressive symptoms .However, in the fully adjusted model which additionally accounted for education, wealth, living arrangement, polypharmacy, and employment, the association between pain intensity and cognitive impairment was no longer significant (OR\u0026thinsp;=\u0026thinsp;1.00, p\u0026thinsp;=\u0026thinsp;0.816), whereas pain interference remained significantly associated (OR\u0026thinsp;=\u0026thinsp;1.01, p\u0026thinsp;=\u0026thinsp;0.038). These findings corroborate previous research showing a positive association between pain interference and cognitive impairment (7, 30\u0026ndash;36).\u003c/p\u003e \u003cp\u003ePrior cross-sectional studies have frequently reported poorer cognitive performance among individuals with chronic pain, particularly in domains such as attention, memory, executive function, and processing speed (37\u0026ndash;39). However, other studies have found no significant associations between pain severity or interference and cognitive dysfunction, highlighting heterogeneity in findings (40, 41). Longitudinal evidence has also been mixed. While one prospective study showed accelerated 10-year cognitive decline associated with persistent pain (8), and another found a correlation between pain intensity and cognitive decline over 2.75 years (42), two longitudinal studies discovered that, pain interference, but not pain intensity, was linked to the cognitive dysfunction (7, 43). Long-term cohort studies have further suggested that chronic pain may be associated with accelerated decline in specific cognitive domains, such as processing speed, independent of depression, medication use, and comorbidities (44, 45). In contrast, some longitudinal analyses have failed to demonstrate a significant association after accounting for confounding factors (46). Meta-analytic evidence has similarly been inconsistent, with one meta-analysis reporting an overall association between pain and cognitive dysfunction (47), while another focusing on longitudinal cohorts found no clear association between chronic pain and incident cognitive impairment (12).\u003c/p\u003e \u003cp\u003eSeveral biological and psychological mechanisms may explain the observed association between pain interference and cognitive impairment. Chronic pain involves sustained engagement of central neural networks implicated in both nociception and cognition, although the precise mechanisms remain incompletely understood (48, 49). Neuroimaging studies have demonstrated that chronic pain is associated with structural and functional alterations in limbic regions, including the hippocampus, amygdala, and cingulate cortex, which play key roles in memory, learning, emotional regulation, and attention (50\u0026ndash;52). Individuals with chronic pain also exhibit a reduction in the volume of the thalamus, insular cortex, and cingulate cortex, which are part of the limbic-related cortex and are involved in executive functions, language, memory, and attention (53, 54). Apkarian et al. demonstrated prefrontal cortex involvement in chronic pain (55). This brain region is essential for higher-level cognitive functions including action planning and execution, goal-directed behavior, and inhibitory control (56, 57). Moreover, alterations in brain structure and connectivity have been linked to maladaptive cognitive processes such as pain catastrophizing, characterized by heightened attention to pain-related stimuli and difficulty disengaging from perceived threats (58\u0026ndash;61). These cognitive-emotional processes may increase cognitive load and limit available cognitive resources, thereby contributing to poorer cognitive performance. Systemic inflammation may represent an additional pathway linking pain and cognitive impairment. Chronic pain has been associated with elevated inflammatory markers, including C-reactive protein (CRP) (45), and inflammation has been implicated in cognitive decline and neurodegenerative processes, including Alzheimer\u0026rsquo;s disease (62). Although inflammatory biomarkers were not directly assessed in the present study, this pathway warrants further investigation in future research.\u003c/p\u003e \u003cp\u003eThe differential associations observed for pain intensity and pain interference may reflect their distinct conceptual meanings. Pain intensity reflects the subjective experience of how severe the pain feels, whereas pain interference measures how much pain affects daily activities and overall quality of life. The differences in their association with cognitive decline may be due to this distinction between the two aspects of pain (63). One possible explanation is that pain interference. encompassing the broader impact of pain on an individual's functional and emotional well-being, likely consumes more cognitive resources than pain that doesn't interfere with daily activities (43, 64).\u003c/p\u003e \u003cp\u003eThe relationship between pain and cognitive function is likely bidirectional. Previous studies have found that higher baseline cognitive performance is associated with lower pain intensity and less interference from pain at follow-up (65, 66). Previous findings strongly support the significant roles of cognitive and emotional factors in the development of chronic pain (67, 68). Cognitive dysfunction in individuals with chronic pain has been shown to be more strongly related to psychological distress and negative affect than to pain intensity itself (69, 70). However, in our study even after adjusting for PHQ-9, pain interference was still associated with cognitive dysfunction. Consistent with prior research, higher levels of depressive symptoms were associated with greater pain interference (71\u0026ndash;73).\u003c/p\u003e \u003cp\u003eFrom a clinical and public health perspective, these findings highlight the importance of assessing pain interference, rather than pain intensity alone, in older adults. Future research should concentrate on the impact of non-pharmacological treatments on the connection between pain and cognitive impairment. By focusing on these strategies, healthcare systems can improve patient outcomes and guide policy decisions on pain management, ultimately enhancing the quality of life for individuals dealing with chronic pain and cognitive decline.\u003c/p\u003e \u003cp\u003eThis study has several limitations that should be acknowledged. First, the observational nature of the data precludes establishing causal relationships between chronic pain and cognitive decline. Second, reliance on self-reported questionnaires to assess pain may introduce recall bias, particularly among older adults who may have impaired memory. Additionally, the study did not account for specific types of pain (e.g., neuropathic, inflammatory), the duration of pain, or the use of pain medications, all of which could influence cognitive outcomes. The absence of these variables limits the granularity of our findings. Future research should utilize prospective longitudinal studies with well-defined pain classifications and thorough cognitive evaluations, while accounting for potential confounders, to better understand the temporal relationships and causal mechanisms connecting chronic pain to cognitive decline and dementia.\u003c/p\u003e \u003cp\u003eDespite these limitations, the study has several important strengths. The large sample size and population-based design of the Birjand Longitudinal Aging Study enhance the statistical power and generalizability of the findings to community-dwelling older adults. Cognitive function was assessed using multiple validated screening instruments, capturing complementary cognitive domains and reducing the likelihood of outcome misclassification based on a single test. In addition, adjustment for a wide range of potential confounders strengthens the robustness of the observed association between pain interference and cognitive impairment. These strengths support the validity of the findings and highlight the importance of distinguishing pain interference from pain intensity in studies of cognitive health in older adults. Future longitudinal studies with detailed pain phenotyping and comprehensive cognitive assessment are warranted to clarify causal pathways linking pain to cognitive decline.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn this population-based study of older adults, pain interference was independently associated with cognitive impairment, whereas pain intensity was not. These findings suggest that the functional impact of pain on daily life may be more relevant to cognitive health than perceived pain severity alone. Differentiating pain dimensions may therefore help identify older individuals at higher risk of cognitive impairment. Clinically, routine assessment of pain interference and interventions targeting pain-related functional limitations may represent modifiable strategies to support cognitive health in aging populations. Future longitudinal studies with detailed pain characterization are needed to clarify causal pathways and underlying mechanisms.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e:\u0026nbsp;This study, part of the Birjand Longitudinal Aging Study (BLAS) in Birjand, Iran, received ethical approval from the Birjand University of Medical Sciences (IR.BUMS.Rec.1397.282) and Tehran University of Medical Sciences\u0026apos; Endocrine and Metabolism Research Institute (IR.TUMS.EMRI.REC.1396.00158). All procedures followed the Declaration of Helsinki. Informed consent was obtained from all participants; for those with cognitive impairment (Abbreviated Mental Test Score \u0026lt; 7), consent was obtained from a close relative or legal guardian. Illiterate participants provided consent via fingerprint after the form was read aloud by a trusted individual.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003e Not applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e: The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e:not applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e:\u0026nbsp;The authors declare that they have no competing interests\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e: There is no specific funding received for this study\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors contributions\u003c/strong\u003e: HE, FS, MM and HF designed and interpreted the result. AR,SR and AS wrote the manuscript which was edited by HE and FS.AR analyzed the results\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003ePetersen RC, Lopez O, Armstrong MJ, Getchius TSD, Ganguli M, Gloss D, et al. Practice guideline update summary: Mild cognitive impairment: Report of the Guideline Development, Dissemination, and Implementation Subcommittee of the American Academy of Neurology. Neurology. 2018;90(3):126-35.\u003c/li\u003e\n\u003cli\u003eWorld Health Organization. Dementia (2021) [Available from: https://www.who.int/news-room/fact-sheets/detail/dementia.\u003c/li\u003e\n\u003cli\u003eOshnouei S, Safaralizade M, Eslamlou NF, Heidari M. Uncovering the extent of dementia prevalence in Iran: a comprehensive systematic review and meta-analysis. BMC Public Health. 2024;24(1):1168.\u003c/li\u003e\n\u003cli\u003eEbadi Fard Azar F, Rezapour A, Bagheri-Faradobeh S, Bagher-Faradonbeh H, Abdolmanafi SH, Jahangiri R. 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Pain. 1994;56(3):289-97.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"aging-clinical-and-experimental-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"acer","sideBox":"Learn more about [Aging Clinical and Experimental Research](http://link.springer.com/journal/40520)","snPcode":"40520","submissionUrl":"https://submission.nature.com/new-submission/40520/3","title":"Aging Clinical and Experimental Research","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Chronic pain, pain interference, cognitive impairment, older adults, Birjand Longitudinal Aging Study","lastPublishedDoi":"10.21203/rs.3.rs-8852522/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8852522/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e: Chronic pain is highly prevalent among older adults and has been shown to be associated with differences in cognitive function. While pain intensity reflects the severity of pain, pain interference assesses the extent to which pain disrupts daily activities. Distinguishing between these dimensions of pain and their associations with cognitive function may improve understanding of how pain relates to cognitive health in older populations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e: This cross-sectional study was conducted on baseline data from the Birjand Longitudinal Aging Study (BLAS). Pain was assessed using the Brief Pain Inventory (BPI), with average pain intensity measured by the BPI-5 score and pain interference by the BPI-9 score. Cognitive impairment was determined based on the combination results of the Six Item Cognitive Impairment Test (6-CIT), the Abbreviated Mental Test Score (AMTS), and the Category Fluency Test (CFT). Multiple logistic regression models were employed to examine associations between pain measures and cognitive impairment, adjusting for potential confounders.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: Among 1,343 participants (mean age: 69.73 ± 7.53 years; 51.82% female), 59.64% were classified as cognitively impaired. In multivariable logistic regression analyses, higher pain interference (BPI-9) was significantly associated with cognitive impairment (OR = 1.01, 95% CI: 1.00–1.03, p = 0.002). Whereas, pain intensity (BPI-5) showed no significant association with cognitive impairment (OR = 1.00, 95% CI: 0.94–1.06, p = 0.019).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e: This study underscores the significant association between pain interference and cognitive impairment in older adults. These findings highlight the importance of addressing pain's impact on daily functioning to mitigate cognitive decline in this population.\u003c/p\u003e","manuscriptTitle":"Associations Between Pain and Cognitive Impairment in Older Adults: Findings from the Birjand Longitudinal Aging Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-20 15:32:19","doi":"10.21203/rs.3.rs-8852522/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-04-01T11:45:36+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-20T16:36:52+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-15T19:02:01+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-05T00:42:27+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"29352997545496559383620369789157819850","date":"2026-02-23T20:12:00+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"326304791874316230545411265722762387450","date":"2026-02-19T23:44:45+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"339744928139056276177740331646118415649","date":"2026-02-19T13:39:12+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"22225337861523614670537837944066561876","date":"2026-02-19T00:30:42+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-18T02:00:20+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-17T13:20:56+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-12T02:58:54+00:00","index":"","fulltext":""},{"type":"submitted","content":"Aging Clinical and Experimental Research","date":"2026-02-11T13:28:13+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"aging-clinical-and-experimental-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"acer","sideBox":"Learn more about [Aging Clinical and Experimental Research](http://link.springer.com/journal/40520)","snPcode":"40520","submissionUrl":"https://submission.nature.com/new-submission/40520/3","title":"Aging Clinical and Experimental Research","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"aca1e5ca-1591-461d-9140-eced15afdd68","owner":[],"postedDate":"February 20th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-18T06:09:21+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-20 15:32:19","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8852522","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8852522","identity":"rs-8852522","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}