Association between Headache and Frailty among Middle-aged and Elderly Individuals: Evidence from the China Health and Retirement Longitudinal Study (CHARLS)

Association between Headache and Frailty among Middle-aged and Elderly Individuals: Evidence from the China Health and Retirement Longitudinal Study (CHARLS) | 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 Article Association between Headache and Frailty among Middle-aged and Elderly Individuals: Evidence from the China Health and Retirement Longitudinal Study (CHARLS) Tianjiao Li, Lingxuan Li, Chenwei li, Kang Wang, Hongyang Xie, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6935511/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Frailty, a clinically recognized geriatric syndrome marked by diminished physiological reserve and heightened vulnerability to adverse health outcomes stemming from multisystem dysregulation, represents a growing global health challenge. This investigation sought to examine the potential association between cephalalgia and incident frailty risk in aging populations. Methods: Leveraging longitudinal data from the China Health and Retirement Longitudinal Study (CHARLS) across 2011-2015 waves, we performed both cross-sectional and prospective cohort analyses involving 17,705 community-dwelling adults aged ≥45 years. Episodic headache was defined as reporting headache either at baseline (2011, Wave 1) or at the follow-up (2015, Wave 3).Chronic headache was defined as reporting headache at both baseline (2011, Wave 1) and at the follow-up endpoint (2015, Wave 3).. Frailty status was quantified using a validated 32-item frailty index (FI) encompassing functional, cognitive, and comorbid conditions. Results: At Wave 1, significant differences were observed between the headache group (n = 1,416) and non-headache group (n = 10,314). The headache group had a higher proportion of females (67.4% vs. 47.4%) and a higher prevalence of comorbidities, including frailty (30.2% vs. 7.8%). They also reported lower engagement in hobbies, smoking, and drinking, as well as shorter sleep duration (5.7 ± 2.1 vs. 6.5 ± 1.7 hours) (all P < 0.001). Logistic regression analysis indicated significantly higher odds of frailty for the headache group in the unadjusted model (OR 5.13, 95% CI 4.48–5.87) and after adjusting for sociodemographic factors (OR 5.39, 95% CI 4.60–6.32) and lifestyle factors (OR 4.22, 95% CI 3.52–5.06) (all P < 0.001). At Wave 3, individuals with chronic headache had markedly elevated odds of frailty (OR 8.30, 95% CI 5.91–11.66) compared to episodic headache (OR 3.71, 95% CI 3.04–4.53). Both chronic (OR 7.98, 95% CI 5.18–12.28) and episodic headaches (OR 3.49, 95% CI 2.73–4.45) remained significantly associated with frailty after adjustments. Subgroup analyses confirmed consistent associations across various demographics, including age and marital status (all P < 0.001). No significant interactions were noted across subgroups. Conclusion: Our study demonstrates that headache is significantly associated with an increased risk of frailty in middle-aged and older adults, with chronic headache showing a more pronounced effect. These results underscore the clinical imperative for optimized headache management strategies as a potential modifiable factor in frailty prevention. Implementing such strategies may concurrently improve geriatric quality of life and reduce the socioeconomic burdens linked to aging-related disability. Health sciences/Health care Health sciences/Neurology Headache Frailty Middle-aged and elderly population China Health and Retirement Longitudinal Study (CHARLS) Figures Figure 1 Figure 2 Figure 3 Introduction The rapid aging of populations worldwide has positioned frailty as a critical public health challenge. Frailty is a well-defined geriatric syndrome marked by diminished physiological reserve and heightened vulnerability to stressors due to multisystem dysregulation [ 1 , 2 ]. This condition is strongly associated with adverse clinical outcomes, including functional disability, increased hospitalization rates, elevated mortality risk, and impaired stress resilience [ 3 , 4 ]. Among frailty assessment tools, the frailty index (FI), which quantifies cumulative age-related health deficits, remains the most widely validated and utilized metric [ 5 ]. Concurrently, headache disorders rank among the most prevalent neurological conditions and a leading cause of global disability [ 6 ]. These disorders are broadly classified into primary headaches (idiopathic conditions such as migraine, tension-type headache, and cluster headache) and secondary headaches (attributable to underlying pathological processes, often carrying significant morbidity and mortality risks) [ 7 ]. Epidemiological studies estimate that primary headache disorders affect 50–75% of adults worldwide, with prevalence rates varying by subtype and geographic region [ 6 , 8 , 9 ]. Previous cross - sectional studies have demonstrated a significant association between headache and stroke [ 10 ]. Another study indicated a correlation between diabetes and chronic headache [ 11 ]. A cohort study also suggested that migraine is related to a higher CVD mortality rate in the US population [ 12 ]. Our prior research revealed a significant link between chronic pain and increased risk of cognitive frailty in middle - aged and elderly individuals [ 13 ]. These studies imply a potential significant association between headache and frailty. Given the substantial healthcare costs and socioeconomic burden imposed by frailty, demonstrating the association between headache and frailty may benefit the prevention of frailty. However, the relationship between headache and frailty remains poorly elucidated, necessitating large-scale prospective cohort studies to clarify this association. In this study, we leveraged data from the China Health and Retirement Longitudinal Study (CHARLS) to provide both cross-sectional and longitudinal evidence on the association between headache disorders and frailty risk. Methods Study population The China Health and Retirement Longitudinal Study (CHARLS) is a nationally representative cohort study designed to collect high-quality microdata on households and individuals aged ≥45 years in China. Its primary objectives are to investigate population aging dynamics and facilitate interdisciplinary gerontological research. The CHARLS national baseline survey employed a multistage probability-proportional-to-size (PPS) sampling strategy to ensure population representativity. The sampling framework included 450 villages/residential committees across 150 counties in 28 provinces, ultimately enrolling >17,000 participants from ~10,000 households. As a longitudinal study with biennial-to-triennial follow-ups, CHARLS has released four waves of publicly available data: wave 1 (2011): National baseline survey, wave 2 (2013): First follow-up, wave 3 (2015): Second follow-up, and wave 4 (2018): Third follow-up. The study protocol was approved by the Institutional Review Board of Peking University (IRB00001052-11015). All participants provided written informed consent prior to enrollment. This investigation utilized data from Waves 1 (2011) and 3 (2015). The Wave 1 cohort comprised 11,730 participants, from which we excluded: 140 cases with missing demographic data (age/sex), 508 participants aged <45 years, 5,321 cases with incomplete frailty index assessments and 9 cases lacking headache-related data. For longitudinal analysis, additional exclusions were applied: 4,971 participants with missing frailty data at Wave 3, 1,228 individuals meeting frailty criteria at baseline (Wave 1). Assessment of headache Pain was evaluated utilizing self-reported symptom inventories, querying: Are you often troubled with any body pains (‘no’ or ‘yes’)? On what part of your body do you feel pain? Please list all parts of your body where you are currently feeling pain (head, neck, chest, stomach, shoulder, back, waist, buttocks, arm, leg, knees, wrist, fingers, ankle, toes) [14]. Consistent with previous studies [14], based on the baseline survey's headache characteristics evaluation, we classified participants into two distinct groups: non-headache and baseline headache. At the follow-up survey conducted 4 years later, headache status was classified into three categories: non-headache, episodic headache, and chronic headache. Episodic headache was defined as reporting headache either at baseline (2011, Wave 1) or at the follow-up (2015, Wave 3). Chronic headache was defined as reporting headache at both baseline (2011, Wave 1) and at the follow-up endpoint (2015, Wave 3). Calculation of frailty index (FI) In accordance with previous methods [15, 16], we employed the Frailty Index (FI) to define frailty. We utilized a previously established 32-item frailty index [15,16], After screening the CHARLS data, 32 items were selected to construct the FI, covering variables related to comorbidity, physical function, disability, depression, and cognition. Except for item 32, each item was dichotomized into 0 (absence of deficit) or 1 (presence of deficit). Item 32 was treated as a continuous variable ranging from 0 to 1, with higher values indicating worse cognition. (Supplementary Table 1). For each participant, the 32-FI was calculated as the sum of present health deficits divided by 32 and multiplied by 100, resulting in a continuous variable ranging from 0 to 100, where higher values indicated a higher degree of frailty. Consistent with previous research, frailty was defined as 32-FI ≥25. Covariates According to prior knowledge, we also considered sociodemographic characteristics and health-related factors in our study. Sociodemographic characteristics included age, gender and marital status (married/unmarried; the term "unmarried" includes several marital statuses: "separated", "unmarried," "divorced" and "widowed") [15]. Ethnicity was defined as a binary variable (Han nationality, other nationalities).Education level was categorized into three distinct groups for analysis: below high School, high School college or above. Health-related factors included ever/current smoke, ever/current alcohol, nighttime sleep duration, andand the remaining four common comorbidities, excluding the ten common comorbidities used to construct the Frailty Index (FI) (dyslipidaemia, Liver disease, kidney disease, digestive system disease). In line with prior studies [17], we defined Hobby as a binary variable. Trained staff posed a standardized question to participants: “In the past month, have you engaged in any social activities listed on this card?” The options were: 1. Playing mahjong, chess, cards, or attending a community club; 2. Attending a sports, social, or other club; 3. Participating in a community organization; 4. Performing volunteer or charity work; 5. Taking an educational or training course; 0. None. Hobby engagement was recorded as a binary indicator (Yes/No) based on participants' responses.Nighttime sleep duration data were obtained from the question ‘‘During the past month, how many hours of actual sleep did you get at night (average hours for one night)?’’. Body mass index (BMI) was defined as the weight divided by the square of height (kg/m 2 ). Health insurance status was ascertained via the Health Insurance Medical Insurance Program survey, wherein participants were required to identify their insurance coverage from a predefined list of options. The classification included: 1) Urban employee medical insurance (yi-bao); 2) Urban resident medical insurance; 3) New cooperative medical insurance (he-zuo-yi-liao); 4) Urban and rural resident medical insurance; 5) Government medical insurance (gong-fei); 6) Medical aid; 7) Private medical insurance procured by the work unit; 8) Private medical insurance procured by the individual; 9) Urban non-employed persons' health insurance; 10) Other specified medical insurance; and 11) No insurance. Participants who indicated 'No insurance' were coded as 'No,' whereas all other responses were coded as 'Yes' for the presence of insurance coverage. Statistical analysis Quantitative data with a normal distribution were described using the mean and standard deviation (SD), while non-normally distributed data were presented using the median (interquartile range). Qualitative data were reported as percentages. Group comparisons between the non-headache, episodic headache and chronic headache groups were carried out using one-way analysis of variance and chi-square tests [18]. In cross-sectional study, a logistic regression model was employed to investigate the association between headache and frailty (Wave 1, 2011), and expressed as odds ratios (OR) and 95% confidence intervals (CI) [18]. Longitudinal data from 2011 and 2015 were analyzed using logistic regression models to explore the relationship between headache and frailty. Four different models with various combinations of covariates were utilized. Specifically, Model 1 included only headache; Model 2 included age, gender, nation, hural and marital status; Model 3 further included education, ever/current smoke, ever/current alcohol, BMI and insurance; Model 4 further included hobby, nighttime sleep duration and co-morbidities [18]. We employed logistic regression analysis (model 4) to perform subgroup analyses on the baseline (2011) and follow-up (2015) datasets [18]. The baseline analysis incorporated gender, age (with a cutoff of 60 years old), marital status, and BMI (with a cutoff of 25 kg/m²) as categorical variables. In the 2015 dataset analysis, building upon the aforementioned subgroups, we further incorporated the frailty status of non-frail individuals into the subgroup analyses. For these participants, health status was defined as FI≤10, while pre-frailty was defined as 10< FI < 32. The aim was to evaluate the influence of these variables on the headache-frailty association within defined subgroups. All statistical analyses were conducted using R software (version 4.4.0; R Foundation for Statistical Computing; http://www.R-­proje ct.org) and Free Statistics software (version2.01; Beijing Free Clinical Medical Technology Co., Ltd)., with a significance level set at 0.05 for all tests [18]. Results Table 1 presents the baseline characteristics of the non-headache group (n = 10,314) and headache group (n = 1,416) at baseline (Wave 1,2011). Significant differences were observed between the groups. The headache group comprised a higher proportion of females (67.4% vs. 47.4%), fewer participants of Han ethnicity 91.7% vs. 92.6%), fewer individuals with a high school education or higher (0.4% vs. 2.6%), and a higher proportion of rural residents (71.1% vs. 55.9%)(all P < 0.001). Regarding lifestyle factors, the headache group reported lower engagement in hobbies (19.4% vs. 28.5%), as well as lower rates of ever/current smoking (30.5% vs. 42.3%) and drinking (32.8% vs. 41.9%). Comorbidity rates were higher in the headache group, including dyslipidemia (13.3% vs. 9.9%), liver disease (5.4% vs. 3.2%), kidney disease (12.7% vs. 4.5%), digestive diseases (38.2% vs. 18.8%), and frailty (30.2% vs. 7.8). Additionally, the headache group exhibited shorter sleep duration (5.7 ± 2.1 vs. 6.5 ± 1.7 hours), a slightly lower BMI (23.1 ± 3.8 vs. 23.5 ± 3.8), and a higher frailty index (median [IQR] 19.5 [13.7, 27.1] vs. 9.2 [4.8, 14.7]). All reported differences were significant (all P 0.05). Table 2 presents the results of logistic regression models assessing the association between headache and frailty in wave1. In the unadjusted model (Model 1), the odds of frailty were significantly higher in the headache group (OR 5.13, 95% CI 4.48–5.87). After adjusting for sociodemographic factors (age, gender, nationality, rural status, and marital status) in Model 2, the association remained significant (OR 5.39, 95% CI 4.60–6.32). Further adjustment for lifestyle and anthropometric variables (education, smoking, alcohol use, BMI, and insurance coverage) in Model 3 marginally increased the odds (OR 5.45, 95% CI 4.60–6.47). In Model 4, which additionally controlled for hobbies, nighttime sleep duration, and comorbidities, the headache group continued to exhibit significantly higher odds of frailty (OR 4.22, 95% CI 3.52–5.06). All models showed a significant association between headache and increased odds of frailty (all P < 0.001). Figure 2 presents subgroup analyses based on Model 4 . The headache group had a significantly higher adjusted odds of frailty (OR 4.22, 95% CI 3.52–5.06) than the non-headache group in the overall population. This association was significant in all age subgroups (<60 years: OR 4.34, 95% CI 3.43–5.5; ≥60 years: OR 4.68, 95% CI 3.71–5.91), marital status subgroups (unmarried: OR 3.85, 95% CI 2.43–6.13; married: OR 4.37, 95% CI 3.67–5.19), and BMI subgroups (<25 kg/m²: OR 4.54, 95% CI 3.68–5.59; ≥25 kg/m²: OR 4.47, 95% CI 3.29–6.05). The association was also significant for those with headache and <6 hours of sleep (OR 3.48, 95% CI 2.75–4.4) compared to those with ≥6 hours (OR 4.2, 95% CI 3.35–5.27). While the association strength varied by gender (females: OR 3.65, 95% CI 3–4.45; males: OR 5.01, 95% CI 3.78–6.63).No significant interactions were observed between headache and these subgroups. (all P-interaction ≥ 0.05). Table 3 presents the results of logistic regression models assessing the association between headache and frailty in wave 3. In the unadjusted model (Model 1), the odds of frailty were significantly higher for individuals with episodic headache (OR 3.71, 95% CI 3.04–4.53) and chronic headache (OR 8.30, 95% CI 5.91–11.66). After adjusting for baseline sociodemographic factors (age, gender, nation, rural status, and marital status) in Model 2, the association remained significantly elevated for both incident (OR 3.49, 95% CI 2.73–4.45) and chronic headache (OR 7.98, 95% CI 5.18–12.28). Further adjustment for lifestyle factors, BMI, and insurance coverage in Model 3 slightly increased the odds for episodic headache (OR 3.71, 95% CI 2.93–4.70) and maintained a significant association for chronic headache (OR 8.70, 95% CI 5.75–13.16). In Model 4, which additionally controlled for hobbies, nighttime sleep duration, and comorbidities, both incident (OR 3.45, 95% CI 2.71–4.41) and chronic headache remained significantly associated with frailty. All models showed a significant association between headache (both incident and chronic) and increased odds of frailty (all P < 0.001). Figure 3 shows subgroup analyses based on Table 3 Model 4. Comparing to the non-headache group, individuals with chronic headache had a significantly higher adjusted odds of frailty (OR 7.95, 95% CI 5.16–12.26), as did those with episodic headache (OR 3.45, 95% CI 2.71–4.41). In age subgroups, both chronic (<60 years: OR 10.42, 95% CI 6.45–16.83; ≥60 years: OR 7.88, 95% CI 3.91–15.89) and episodic headache (<60 years: OR 3.71, 95% CI 2.72–5.06; ≥60 years: OR 3.75, 95% CI 2.67–5.26) were associated with higher odds of frailty. By gender, females with chronic headache had an OR of 7.23 (95% CI 4.68–11.18) and males 8.59 (95% CI 3.69–20.02), while females with episodic headache had an OR of 2.81 (95% CI 2.13–3.71) and males 4.15 (95% CI 2.84–6.06). In the marital status subgroup, both unmarried (OR 13.31, 95% CI 2.42–73.06) and married (OR 8.68, 95% CI 5.82–12.93) individuals with chronic headache had higher odds of frailty than the non-headache group. For episodic headache, unmarried individuals had an OR of 2.53 (95% CI 1.30–4.92) and married individuals 3.61 (95% CI 2.84–4.58). For BMI groups, chronic headache was associated with higher odds in both <25 kg/m² (OR 9.71, 95% CI 6.03–15.65) and ≥25 kg/m² (OR 3.58, 95% CI 1.58–8.07) subgroups. Episodic headache also showed elevated odds in both BMI subgroups (<25 kg/m² OR 3.36, 95% CI 2.49–4.55; ≥25 kg/m² OR 3.48, 95% CI 2.39–5.07). Regarding nighttime sleep duration, chronic headache had higher odds in both <6 hours (OR 6.80, 95% CI 3.76–12.32) and ≥6 hours (OR 8.42, 95% CI 5.03–14.12) subgroups. Episodic headache had elevated odds in the <6 hours subgroup (OR 2.92, 95% CI 2.00–4.27) and slightly lower in the ≥6 hours subgroup (OR 3.52, 95% CI 2.67–4.65). In the frailty group subgroup, chronic headache in the pre-frailty group had an OR of 8.30 (95% CI 2.47–27.92) compared to the healthy group, while episodic headache had an OR of 2.29 (95% CI 1.13–4.63). In the healthy group, episodic headache had an OR of 2.32 (95% CI 1.82–2.96) and chronic headache 4.71 (95% CI 3.12–7.10). Notably, no significant interactions were observed across any of the subgroups. Discussion According to our cross-sectional study, the incidence of frailty was significantly higher in individuals with headache than those without headache, and in our longitudinal study, individuals with episodic and chronic headache had a higher risk of developing frailty compared to those without headache. Subgroup analyses confirmed consistent associations across various demographics, including age and marital status. No significant interactions were noted across subgroups. With the exponential growth of the global aging population, frailty has become a prevalent health concern. Extensive research has established a significant association between frailty and pain. Chronic pain has been shown to have a robust positive correlation with frailty [ 19 – 21 ]. Empirical studies have demonstrated that approximately 40–50% of frail elderly individuals concurrently experience chronic pain [ 22 , 23 ]. Elderly individuals with chronic pain are at a higher risk of developing frailty compared to those without chronic pain. In a longitudinal cohort study with an 8-year follow-up, pain alone was found to contribute to a substantial proportion of frailty cases compared to pain-free individuals [ 21 ]. Blyth et al. were the first to report that individuals meeting ≥ 3 frailty phenotype criteria are more likely to report pain [ 24 ]. Furthermore, frailty has been identified as an independent predictor of both acute and chronic postoperative pain (APSP and CPSP) following total knee arthroplasty (TKA) in older patients [ 25 ], and frail individuals are at a higher risk of developing chronic pain following cardiac surgery [ 26 ]. Similarly, a U-shaped relationship has been observed between the Frailty Index (FI) and the prevalence of low back pain (LBP) among middle-aged and older adults in China, indicating that both extremely low and high levels of frailty are associated with an increased risk of LBP [ 27 ]. In hospitalized cancer patients, the FI has been shown to correlate with the presence and intensity of persistent pain [ 28 ]. Additionally, frailty is associated with more severe pain trajectories; frail individuals are 5–6 times more likely than robust individuals to experience severe or very severe pain trajectories over a 9-year follow-up [ 29 ]. Further longitudinal studies have confirmed the bidirectional relationship between frailty and pain [ 30 ]. Collectively, these studies suggest a bidirectional relationship between pain and frailty, where in pain predicts the development of frailty, and frailty predicts the development or exacerbation of pain. However, no studies discuss the relationship between headache and frailty. As primary headache affects approximately 50–75% of adults globally [ 6 , 8 , 9 ], it is of vital importance to explore the relationship between headache and frailty. In this study, the incidence of frailty was significantly higher in individuals with headache than those without headache, and in our longitudinal study, individuals with episodic and chronic headache had a higher risk of frailty compared to those without headache. To our knowledge, this study is the first to investigate the association between headache and frailty. The pathophysiological mechanisms underlying the pain-frailty association may also explain the relationship between headache and frailty. First, chronic pain contributes to reduced mobility, lower resting metabolic rate, and diminished nutritional intake, all of which are hallmarks of frailty. Second, sustained pain activates the hypothalamic-pituitary-adrenal (HPA) axis, leading to hypercortisolemia [ 31 – 33 ], a known contributor to frailty development. Third, pro-inflammatory signaling and immune dysregulation mediate the bidirectional relationship between chronic pain and frailty [ 34 ]. Furthermore, persistent pain may induce neurostructural changes, including gray matter atrophy and white matter tract degeneration, potentially impairing neural network efficiency [ 35 , 36 ]. The mechanisms underlying headache and frailty calls for further exploration. This study possesses several methodological strengths. First, utilizing nationally representative data from the China Health and Retirement Longitudinal Study (CHARLS), it enabled a robust assessment of the association between headache and frailty in the aging Chinese population. Second, the large sample size surpassed those of prior comparable studies, enhancing statistical power. Third, the combined cross-sectional and longitudinal analyses strengthened the evidence for this association. However, several limitations should be acknowledged. The retrospective design limited comprehensive adjustment for potential confounders. Additionally, a substantial proportion of CHARLS data contained missing or incomplete entries, which may have introduced bias. Furthermore, diagnoses within CHARLS primarily relied on self-reported questionnaires, potentially leading to recall bias and misclassification (e.g., undiagnosed cases categorized as healthy). Future prospective cohort studies are needed to better elucidate the temporal relationship between headache progression and frailty. Conclusion In this nationwide cohort study, we demonstrated that both incident and chronic headache were significantly associated with higher prevalence of frailty. Notably, headache sufferers exhibited elevated risks of developing pre-frailty and frailty states in the middle-aged and elderly Chinese population. Given that headache disorders may potentially contribute to the pathogenesis of frailty, effective headache management could serve as a crucial intervention for frailty prevention. This dual approach would not only enhance quality of life in aging populations but also alleviate the socioeconomic burden associated with geriatric care. Declarations Ethics approval and consent to participate The CHARLS survey project received ethical approval from the Biomedical Ethics Committee of Peking University（IRB00001052-11015） Consent for publication Not applicable Availability of data and materials The datasets used during the current study are available from the CHARLS database. Competing interests The authors declare that they have no competing interests. Funding None. Authors' contributions TJL and LXL analyzed and interpreted the data of the CHARLS. CWL and KW made the tables and figures of the manuscript. HYX wrote the outline of the manuscript. BS analyzed the data and wrote the manuscript. CDW checked the manuscript, the tables and figures. Data availability The datasets used and/or analysed during the current study available from the corresponding author on reasonable request. Acknowledgements We thank the researchers of the CHARLS database for providing public data for the research. References Clegg A, Young J, Iliffe S, Rikkert MO, Rockwood K. Frailty in elderly people. Lancet. 2013;381(9874):752-762. https://doi.org/10.1016/S0140-6736(12)62167-0. Robertson DA, Savva GM, Kenny RA. Frailty and cognitive impairment: a review of the evidence and causal mechanisms. Ageing Res Rev. 2013;12(4):840-851. https://doi.org/10.1016/j.arr.2013.06.002. Cesari M, Calvani R, Marzetti E. Frailty in older persons. Clin Geriatr Med. 2017;33(2):293-303. https://doi.org/10.1016/j.cger.2017.02.002IF: 3.1 Q3 . Fried LP, Tangen CM, Walston J, et al. Frailty in older adults: evidence for a phenotype. J Gerontol A Biol Sci Med Sci. 2001;56(3):M146-M156. https://doi.org/10.1093/gerona/56.3.m146. Searle SD, Mitnitski A, Gahbauer EA, Gill TM, Rockwood K. A standard procedure for creating a frailty index. BMC Geriatr. 2008;8(1):24. https://doi.org/10.1186/1471-2318-8-24. GBD 2016 Neurology Collaborators. Global, regional, and national burden of neurological disorders, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet Neurol. 2019;18(4):459-480. https://doi.org/10.1016/S1474-4422(19)30016-9. Giamberardino MA, Affaitati G, Costantini R, Guglielmetti M, Martelletti P. Acute headache management in emergency department: a narrative review. Intern Emerg Med. 2020;15(1):109-117. https://doi.org/10.1007/s10194-019-01042-z. Steiner TJ, Stovner LJ, Chowdhury DI, et al. Migraine remains second among the world’s causes of disability, and first among young women: findings from GBD2019. J Headache Pain. 2020;21(1):137. https://doi.org/10.1186/s10194-020-01208-0. Vetvik KG, MacGregor EA. Sex differences in the epidemiology, clinical features, and pathophysiology of migraine. Lancet Neurol. 2017;16(1):76-87. https://doi.org/10.1016/S1474-4422(16)30293-9. Wang MH, Pan LJ, Zhang YH, et al. Prevalence and risk factors of headache in Chinese with stroke: a cross-sectional study based on CHARLS. J Headache Pain. 2024;25(1):1-10. https://doi.org/10.1186/s10194-024-01930-z. Min D, Anle D, Lijie Z, Xiaoyun X. The impact of diabetes on chronic pain in different body regions among adults aged 50 and older: a cross-sectional analysis. Front Public Health. 2025;13:0. https://doi.org/10.3389/fpubh.2025.1520735. Liu HX, Zhang SH, Gong ZH, et al. Association between migraine and cardiovascular disease mortality: A prospective population-based cohort study. Headache. 2023 Sep;63(8):1109-1118. https://doi.org/10.1111/head.14616. Li TJ, Li LX, Xie HY, et al. Association between chronic pain and cognitive frailty among middle-aged and elderly individuals: evidence from the China Health and Retirement Longitudinal Study. Front Aging Neurosci. 2024;16:0. https://doi.org/10.3389/fnagi.2024.1491120. Chen JT, Yan LY, Chu JJ, Wang XY, Xu ZR. Pain Characteristics and Progression to Sarcopenia in Chinese Middle-Aged and Older Adults: A 4-Year Longitudinal Study. J Gerontol A Biol Sci Med Sci. 2024;79(5):1-10. https://doi.org/10.1093/gerona/glae080. Xie X, Que J, Sun L, et al. Association between urbanization levels and frailty among middle-aged and older adults in China: evidence from the CHARLS. BMC Medicine. 2025;23(1):0-0. https://doi.org/10.1186/s12916-025-03961-y. He D, Qiu YW, Yan MS, et al. Associations of metabolic heterogeneity of obesity with frailty progression: Results from two prospective cohorts. J Cachexia Sarcopenia Muscle. 2023;14(1):632-641. https://doi.org/10.1002/jcsm.13169. Mak HW, Noguchi T, Bone JK, et al. Hobby engagement and mental wellbeing among people aged 65 years and older in 16 countries. Nat Med. 2023;29(8):2233-2240. https://doi.org/10.1038/s41591-023-02506-1. Tianjiao Li, Lingxuan Li, Hongyang Xie, Rongyu Ping, Yane Guo, Dongmei Li, Yuwei Zhang, Xiujuan Bai and Bo Sun. Association between chronic pain and cognitive frailty among middle-aged and elderly individuals: evidence from the China Health and Retirement Longitudinal Study. Frontiers in Aging Neuroscience. 10.3389/fnagi.2024.1491120. Blyth FM, Rochat S, Cumming RG, et al. Pain, frailty and comorbidity in older men: The CHAMP study. Pain. 2008;140(1):224-230. https://doi.org/10.1016/j.pain.2008.08.011. Coelho T, Paul C, Gobbens RJJ, Fernandes L. Multidimensional frailty and pain in community-dwelling elderly. Pain Med. 2017;18(4):693-701. https://doi.org/10.1111/pme.12746. Wade KF, Marshall A, Vanhoutte B, et al. Does pain predict frailty in older men and women? Findings from the English Longitudinal Study of Ageing (ELSA). J Gerontol A Biol Sci Med Sci. 2017;72(3):403-409. https://doi.org/10.1093/gerona/glw226. Chang CI, Chan DC, Kuo KN, Hsiung CA, Chen CY. Prevalence and correlates of geriatric frailty in a northern Taiwan community. J Formos Med Assoc. 2011;110(4):247-257. https://doi.org/10.1016/S0929-6646(11)60037-5. Shega JW, Andrew M, Kotwal A, et al. Relationship between persistent pain and 5-year mortality: A population-based prospective cohort study. J Am Geriatr Soc. 2013;61(12):2135-2141. https://doi.org/10.1111/jgs.12554. Blyth FM, Rochat S, Cumming RG, et al. Pain, frailty and comorbidity in older men: the CHAMP study. Pain. 2008;140(1):224-230. https://doi.org/10.1016/j.pain.2008.08.011. Jin Y, Tang S, Wang W, et al. Preoperative frailty predicts postoperative pain after total knee arthroplasty in older patients: a prospective observational study. Eur Geriatr Med. 2024;15(3):657-665. https://doi.org/10.1007/s41999-024-00932-z. Arends BC, Timmerman L, Vernooij LM, et al. Preoperative frailty and chronic pain after cardiac surgery: a prospective observational study. BMC Anesthesiol. 2022;22(1):201. https://doi.org/10.1186/s12871-022-01746-x. Qing L, Zhu Y, Feng L, et al. Exploring the association between Frailty index and low back pain in middle-aged and older Chinese adults: a cross-sectional analysis of data from the China Health and Retirement Longitudinal Study (CHARLS). BMJ Open. 2024;14(3):e085645. https://doi.org/10.1136/bmjopen-2024-085645. Crosignani S, Orlandini L, Baruffi S, et al. Frailty and persistent pain in oncological patients undergoing rehabilitation. J Frailty Aging. 2022;11(3):286-290. https://doi.org/10.14283/jfa.2022.26. Cai G, Zhang Y, Wang Y, et al. Frailty predicts knee pain trajectory over 9 years: results from the osteoarthritis initiative. Pain Med. 2023;24(6):1364-1371. https://doi.org/10.1093/pm/pnad097. Chaplin WJ, McWilliams DF, Millar BS, et al. The bidirectional relationship between chronic joint pain and frailty: data from the investigating musculoskeletal health and wellbeing cohort. BMC Geriatr. 2023;23(1):273. https://doi.org/10.1186/s12877-023-03949-4. McBeth J, Chiu YH, Silman AJ, et al. Hypothalamic-pituitary-adrenal stress axis function and the relationship with chronic widespread pain and its antecedents. Arthritis Res Ther. 2005;7(5):R992-R1000. https://doi.org/10.1186/ar1826. Choi C-J, Knudsen R, Oda K, et al. The association between incident self-reported fibromyalgia and nonpsychiatric factors: 25 years follow-up of the Adventist Health Study. J Pain. 2010;62(6):611-617. https://doi.org/10.1016/j.jpain.2010.03.002. Varadhan R, Walston J, Cappola AR, et al. Higher levels and blunted diurnal variation of cortisol in frail older women. J Gerontol A Biol Sci Med Sci. 2008;63(2):190-195. https://doi.org/10.1093/gerona/63.2.190. Edwards RR, Kronfli T, Haythornthwaite JA, et al. Association of catastrophizing with interleukin-6 responses to acute pain. Pain. 2008;140(1):135-144. https://doi.org/10.1016/j.pain.2008.07.003. Malfliet A, Coppieters I, Van Wilgen P, et al. Brain changes associated with cognitive and emotional factors in chronic pain: a systematic review. Eur J Pain. 2017;21(3):769-786. https://doi.org/10.1002/ejp.978. Gomez-Beldarrain M, Oroz I, Zapirain BG, et al. Right fronto-insular white matter tracts link cognitive reserve and pain in migraine patients. J Headache Pain. 2016;17(1):4. https://doi.org/10.1186/s10194-016-0600-9. Tables Table1 Baseline characteristics of study population in wave 1 Total (n = 11730) Non-headache(n = 10314) Headache(n = 1416) P value Age(years, M ± SD) 58.3 ± 9.0 58.4 ± 9.0 58.1 ± 8.7 0.234 Gender, n (%) < 0.001 Female 5839 (49.8) 4885 (47.4) 954 (67.4) Male 5891 (50.2) 5429 (52.6) 462 (32.6) Marital, n (%) 0.075 Married 1287 (11.0) 1112 (10.8) 175 (12.4) Unmarried 10443 (89.0) 9202 (89.2) 1241 (87.6) Ethnic group , n (%) <0.001 Other 712 ( 7.5) 615 (7.4) 97 (8.3) Han 8735 (92.5) 7657 (92.6) 1078 (91.7) Education, n (%) < 0.001 Below high school 10085 (86.0) 8755 (84.9) 1330 (93.9) High school 1370 (11.7) 1289 (12.5) 81 (5.7) College or above 275 ( 2.3) 270 (2.6) 5 (0.4) Residence , n (%) < 0.001 No 4954 (42.2) 4545 (44.1) 409 (28.9) Yes 6776 (57.8) 5769 (55.9) 1007 (71.1) Hobby, n (%) < 0.001 No 8516 (72.6) 7375 (71.5) 1141 (80.6) Yes 3213 (27.4) 2938 (28.5) 275 (19.4) Ever/current smoke, n (%) < 0.001 No 6931 (59.1) 5947 (57.7) 984 (69.5) Yes 4798 (40.9) 4366 (42.3) 432 (30.5) Ever/current drink, n (%) < 0.001 No 6944 (59.2) 5993 (58.1) 951 (67.2) Yes 4783 (40.8) 4318 (41.9) 465 (32.8) Insurance, n (%) 0.458 No 714 ( 6.1) 634 (6.2) 80 (5.7) Yes 10981 (93.9) 9648 (93.8) 1333 (94.3) Comorbidities Dyslipidemia, n (%) < 0.001 No 10430 (89.7) 9214 (90.1) 1216 (86.7) Yes 1199 (10.3) 1012 (9.9) 187 (13.3) LiverDisease, n (%) < 0.001 No 11311 (96.6) 9977 (96.8) 1334 (94.6) Yes 402 ( 3.4) 326 (3.2) 76 (5.4) KidneyDisease, n (%) < 0.001 No 11068 (94.5) 9836 (95.5) 1232 (87.3) Yes 639 ( 5.5) 459 (4.5) 180 (12.7) DigestiveDisease, n (%) < 0.001 No 9241 (78.8) 8369 (81.2) 872 (61.8) Yes 2480 (21.2) 1940 (18.8) 540 (38.2) Frailty, n (%) < 0.001 No 10502 (89.5) 9513 (92.2) 989 (69.8) Yes 1228 (10.5) 801 (7.8) 427 (30.2) Nighttime sleep duration, M ± SD 6.4 ± 1.8 6.5 ± 1.7 5.7 ± 2.1 < 0.001 BMI, M ± SD 23.5 ± 3.8 23.5 ± 3.8 23.1 ± 3.8 < 0.001 Frailty Index,Median (IQR) 10.7 (5.1, 17.3) 9.2 (4.8, 14.7) 19.5 (13.7, 27.1) < 0.001 Abbreviations: BMI, body mass index; M± SD, mean ± standard deviation. IQR, interquartile range. T able2 Logistic regression model on headache and frailty in wave 1 Headache Model Model1 Model2 Model3 Model4 OR (95% CI) P-value OR(95% CI) P-value OR(95% CI) P-value OR(95% CI) P-value Non-headache 1(Ref) 1(Ref) 1(Ref) 1(Ref) Headache 5.13 (4.48~5.87) <0.001 5.39 (4.6~6.32) <0.001 5.45 (4.6~6.47) <0.001 4.22 (3.52~5.06) <0.001 Notes: Model 1: No adjustment; Model 2: Adjusted for age, gender, ethnic group, hural and marital status; Model 3: Model 2 + education,ever/current smoke,ever/current alcohol,BMI, insurance; Model 4: Model 3 +hobby,Nighttime sleep duration, Comorbidities T able3 Logistic regression model on Headache and Frailty at 2015 Headache Model Model1 Model2 Model3 Model4 OR (95% CI) P-value OR(95% CI) P-value OR(95% CI) P-value OR(95% CI) P-value Non-headache 1(Ref) 1(Ref) 1(Ref) 1(Ref) Episodic Headache 3.71 (3.04~4.53) <0.001 3.49 (2.73~4.45) <0.001 3.71 (2.93~4.7) <0.001 3.45 (2.71~4.41) <0.001 Chronic Headache 8.3 (5.91~11.66) <0.001 7.98 (5.18~12.28) <0.001 8.70 (5.75~13.16) <0.001 7.95 (5.16~12.26) <0.001 Notes: Model 1: No adjustment; Model 2: Adjusted for age, gender, ethnic group, hural and marital status; Model 3: Model 2 + education,ever/current smoke,ever/current alcohol,BMI,insurance; Model 4: Model 3 +hobby,Nighttime sleep duration, Comorbidities Additional Declarations No competing interests reported. Supplementary Files TableS1.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6935511","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":498238618,"identity":"dfb443b0-9505-42fd-b183-6d477f03db88","order_by":0,"name":"Tianjiao Li","email":"","orcid":"","institution":"Capital Medical University","correspondingAuthor":false,"prefix":"","firstName":"Tianjiao","middleName":"","lastName":"Li","suffix":""},{"id":498238622,"identity":"2f80e294-195c-457c-8c45-6df943d08337","order_by":1,"name":"Lingxuan Li","email":"","orcid":"","institution":"Beijing Forestry University","correspondingAuthor":false,"prefix":"","firstName":"Lingxuan","middleName":"","lastName":"Li","suffix":""},{"id":498238624,"identity":"52811424-e0ec-4174-953d-1934695885ba","order_by":2,"name":"Chenwei li","email":"","orcid":"","institution":"No.989 Hospital of Joint Logistic Support Force of PLA","correspondingAuthor":false,"prefix":"","firstName":"Chenwei","middleName":"","lastName":"li","suffix":""},{"id":498238627,"identity":"dfe587da-d5dc-4d11-b0df-0128c7c744fe","order_by":3,"name":"Kang Wang","email":"","orcid":"","institution":"The First Affiliated Hospital of Army Medical University","correspondingAuthor":false,"prefix":"","firstName":"Kang","middleName":"","lastName":"Wang","suffix":""},{"id":498238629,"identity":"5e9f0713-0177-467b-afbb-af3ea7f2752d","order_by":4,"name":"Hongyang Xie","email":"","orcid":"","institution":"Chinese PLA General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Hongyang","middleName":"","lastName":"Xie","suffix":""},{"id":498238630,"identity":"c68f1383-7d70-4714-b0c3-39e43d1e5703","order_by":5,"name":"Chaodong Wang","email":"","orcid":"","institution":"Capital Medical University","correspondingAuthor":false,"prefix":"","firstName":"Chaodong","middleName":"","lastName":"Wang","suffix":""},{"id":498238632,"identity":"56287d63-4dff-4668-b1f9-8cd5c99fd335","order_by":6,"name":"Bo Sun","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5klEQVRIiWNgGAWjYLACxgYYy8CGh5+/AbdKVC1sYC1pMpIzDpCkheGwjUFDAn7V8jNyjz3m3WEjxyDf+/DDj4LzPAYMBxg/fMzBrcXgRl66Me+ZNGMGNnZjyR6D2zzmzA3MkjO34dEikWMmzdt2OLGBjY1BmgGoxbLhABszLx4t8jMQWph/Mxic4zE4kIBfC8MNhBY2oC0HCGsxOPPGTHIu2C9pbJY9Bsk8kjMONuP1i3x7jpnEW1CIMR9jvvHjj509P3/zwQ8f8TkMCJh4gIT9ATgfkRhwAsYfBJWMglEwCkbBiAYAKAZHcADq2q4AAAAASUVORK5CYII=","orcid":"","institution":"Capital Medical University","correspondingAuthor":true,"prefix":"","firstName":"Bo","middleName":"","lastName":"Sun","suffix":""}],"badges":[],"createdAt":"2025-06-20 05:38:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6935511/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6935511/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":88995779,"identity":"c2f90bcd-d3c9-493c-bc18-7a9b65abfee6","added_by":"auto","created_at":"2025-08-13 14:29:53","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":180950,"visible":true,"origin":"","legend":"\u003cp\u003eThe flowchart of thesample selection process.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-6935511/v1/568fcb5bce9709645c4fd869.png"},{"id":88994154,"identity":"63acf0fd-83a7-441d-857b-ce93781cc320","added_by":"auto","created_at":"2025-08-13 14:13:53","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":288148,"visible":true,"origin":"","legend":"\u003cp\u003eAssociation between baseline headache status (Wave 1) and frailty prevalence across demographic and clinical subgroups, with covariate adjustments equivalent to Model 4.Squares indicate subgroup-specific odds ratios (ORs), while horizontal lines depict their corresponding 95% confidence intervals (CIs). Diamonds represent pooled overall estimates, with lateral diamond tips marking the 95% CIs for meta-analyzed risks. Analyses were adjusted for age, sex, education, socioeconomic status, comorbidities, and BMI (see Model 4 for full covariate specifications).Abbreviations: BMI, body mass index; CI, confidence interval; OR, odds ratio.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-6935511/v1/e7c862edf026bf2a3222fbd7.png"},{"id":88994157,"identity":"91902061-7301-4c20-bf71-d45c84188885","added_by":"auto","created_at":"2025-08-13 14:13:53","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":586647,"visible":true,"origin":"","legend":"\u003cp\u003eSubgroup associations between headache in wave 3 and frailty, adjusted for covariates as specified in Model 4. Squares denote subgroup-specific odds ratios (ORs), with horizontal lines indicating 95% confidence intervals (CIs). Diamonds indicate pooled risk estimates, and the lateral tips of the diamonds delineate the 95% CIs for these pooled estimates. Abbreviations: BMI, body mass index; CI, confidence interval; OR, odds ratio.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-6935511/v1/b9919dd5291e5b0e1b8037d2.png"},{"id":89352791,"identity":"d26f7cdb-748c-497a-bcac-4bdda309b453","added_by":"auto","created_at":"2025-08-19 06:39:00","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1499403,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6935511/v1/38c801fa-f270-4cfc-b740-ab5a0ce40d23.pdf"},{"id":88994647,"identity":"167ce4af-027b-4854-9827-da4e25d6ecf4","added_by":"auto","created_at":"2025-08-13 14:21:53","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":19510,"visible":true,"origin":"","legend":"","description":"","filename":"TableS1.docx","url":"https://assets-eu.researchsquare.com/files/rs-6935511/v1/49a830760ba4b51ebe6b261f.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Association between Headache and Frailty among Middle-aged and Elderly Individuals: Evidence from the China Health and Retirement Longitudinal Study (CHARLS)","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe rapid aging of populations worldwide has positioned frailty as a critical public health challenge. Frailty is a well-defined geriatric syndrome marked by diminished physiological reserve and heightened vulnerability to stressors due to multisystem dysregulation [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. This condition is strongly associated with adverse clinical outcomes, including functional disability, increased hospitalization rates, elevated mortality risk, and impaired stress resilience [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Among frailty assessment tools, the frailty index (FI), which quantifies cumulative age-related health deficits, remains the most widely validated and utilized metric [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eConcurrently, headache disorders rank among the most prevalent neurological conditions and a leading cause of global disability [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. These disorders are broadly classified into primary headaches (idiopathic conditions such as migraine, tension-type headache, and cluster headache) and secondary headaches (attributable to underlying pathological processes, often carrying significant morbidity and mortality risks) [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Epidemiological studies estimate that primary headache disorders affect 50–75% of adults worldwide, with prevalence rates varying by subtype and geographic region [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Previous cross - sectional studies have demonstrated a significant association between headache and stroke [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Another study indicated a correlation between diabetes and chronic headache [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. A cohort study also suggested that migraine is related to a higher CVD mortality rate in the US population [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Our prior research revealed a significant link between chronic pain and increased risk of cognitive frailty in middle - aged and elderly individuals [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. These studies imply a potential significant association between headache and frailty.\u003c/p\u003e\u003cp\u003eGiven the substantial healthcare costs and socioeconomic burden imposed by frailty, demonstrating the association between headache and frailty may benefit the prevention of frailty. However, the relationship between headache and frailty remains poorly elucidated, necessitating large-scale prospective cohort studies to clarify this association.\u003c/p\u003e\u003cp\u003eIn this study, we leveraged data from the China Health and Retirement Longitudinal Study (CHARLS) to provide both cross-sectional and longitudinal evidence on the association between headache disorders and frailty risk.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eStudy population\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe China Health and Retirement Longitudinal Study (CHARLS) is a nationally representative cohort study designed to collect high-quality microdata on households and individuals aged \u0026ge;45 years in China. Its primary objectives are to investigate population aging dynamics and facilitate interdisciplinary gerontological research.\u003c/p\u003e\n\u003cp\u003eThe CHARLS national baseline survey employed a multistage probability-proportional-to-size (PPS) sampling strategy to ensure population representativity. The sampling framework included 450 villages/residential committees across 150 counties in 28 provinces, ultimately enrolling \u0026gt;17,000 participants from ~10,000 households.\u003c/p\u003e\n\u003cp\u003eAs a longitudinal study with biennial-to-triennial follow-ups, CHARLS has released four waves of publicly available data: wave 1 (2011): National baseline survey, wave 2 (2013): First follow-up, wave 3 (2015): Second follow-up, and wave 4 (2018): Third follow-up. The study protocol was approved by the Institutional Review Board of Peking University (IRB00001052-11015). All participants provided written informed consent prior to enrollment. This investigation utilized data from Waves 1 (2011) and 3 (2015). The Wave 1 cohort comprised 11,730 participants, from which we excluded: 140 cases with missing demographic data (age/sex), 508 participants aged \u0026lt;45 years, 5,321 cases with incomplete frailty index assessments and 9 cases lacking headache-related data. For longitudinal analysis, additional exclusions were applied: 4,971 participants with missing frailty data at Wave 3, 1,228 individuals meeting frailty criteria at baseline (Wave 1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAssessment of headache\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePain was evaluated utilizing self-reported symptom inventories, querying: Are you often troubled with any body pains (\u0026lsquo;no\u0026rsquo;\u0026nbsp;or\u0026nbsp;\u0026lsquo;yes\u0026rsquo;)? On what part of your body do you feel pain? Please list all parts of your body where you are currently feeling pain (head, neck, chest, stomach, shoulder, back, waist, buttocks, arm, leg, knees, wrist, fingers, ankle, toes) [14]. Consistent with previous studies [14], based on the baseline survey\u0026apos;s headache characteristics evaluation, we classified participants into two distinct groups: non-headache and baseline headache. At the follow-up survey conducted 4 years later, headache status was classified into three categories: non-headache, episodic headache, and chronic headache. Episodic headache was defined as reporting headache either at baseline (2011, Wave 1) or at the follow-up (2015, Wave 3). Chronic headache was defined as reporting headache at both baseline (2011, Wave 1) and at the follow-up endpoint (2015, Wave 3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCalculation of frailty index (FI)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn accordance with previous methods [15, 16], we employed the Frailty Index (FI) to define frailty. We utilized a previously established 32-item frailty index [15,16], After screening the CHARLS data, 32 items were selected to construct the FI, covering variables related to comorbidity, physical function, disability, depression, and cognition. Except for item 32, each item was dichotomized into 0 (absence of deficit) or 1 (presence of deficit). Item 32 was treated as a continuous variable ranging from 0 to 1, with higher values indicating worse cognition. (Supplementary Table 1). For each participant, the 32-FI was calculated as the sum of present health deficits divided by 32 and multiplied by 100, resulting in a continuous variable ranging from 0 to 100, where higher values indicated a higher degree of frailty. Consistent with previous research, frailty was defined as 32-FI \u0026ge;25.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCovariates\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAccording to prior knowledge, we also considered sociodemographic characteristics and health-related factors in our study. Sociodemographic characteristics included age, gender and marital status (married/unmarried; the term \u0026quot;unmarried\u0026quot; includes several marital statuses: \u0026quot;separated\u0026quot;, \u0026quot;unmarried,\u0026quot; \u0026quot;divorced\u0026quot; and \u0026quot;widowed\u0026quot;) [15].\u0026nbsp;Ethnicity was defined as a binary variable (Han nationality, other nationalities).Education level was categorized into three distinct groups for analysis: below high School, high School college or above. Health-related factors included ever/current smoke, ever/current alcohol, nighttime sleep duration, andand the remaining four common comorbidities, excluding the ten common comorbidities used to construct the Frailty Index (FI) (dyslipidaemia, Liver disease, kidney disease, digestive system disease). In line with prior studies [17], we defined Hobby as a binary variable. Trained staff posed a standardized question to participants: \u0026ldquo;In the past month, have you engaged in any social activities listed on this card?\u0026rdquo; The options were: 1. Playing mahjong, chess, cards, or attending a community club; 2. Attending a sports, social, or other club; 3. Participating in a community organization; 4. Performing volunteer or charity work; 5. Taking an educational or training course; 0. None. Hobby engagement was recorded as a binary indicator (Yes/No) based on participants\u0026apos; responses.Nighttime sleep duration data were obtained from the question \u0026lsquo;\u0026lsquo;During the past month, how many hours of actual sleep did you get at night (average hours for one night)?\u0026rsquo;\u0026rsquo;. Body mass index (BMI) was defined as the weight divided by the square of height (kg/m\u003csup\u003e2\u003c/sup\u003e). Health insurance status was ascertained via the Health Insurance Medical Insurance Program survey, wherein participants were required to identify their insurance coverage from a predefined list of options. The classification included: 1) Urban employee medical insurance (yi-bao); 2) Urban resident medical insurance; 3) New cooperative medical insurance (he-zuo-yi-liao); 4) Urban and rural resident medical insurance; 5) Government medical insurance (gong-fei); 6) Medical aid; 7) Private medical insurance procured by the work unit; 8) Private medical insurance procured by the individual; 9) Urban non-employed persons\u0026apos; health insurance; 10) Other specified medical insurance; and 11) No insurance. Participants who indicated \u0026apos;No insurance\u0026apos; were coded as \u0026apos;No,\u0026apos; whereas all other responses were coded as \u0026apos;Yes\u0026apos; for the presence of insurance coverage.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eQuantitative data with a normal distribution were described using the mean and standard deviation (SD), while non-normally distributed data were presented using the median (interquartile range). Qualitative data were reported as percentages. Group comparisons between the non-headache, episodic headache and chronic headache groups were carried out using one-way analysis of variance and chi-square tests [18].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn cross-sectional study, a logistic regression model was employed to investigate the association between headache and frailty (Wave 1, 2011), and expressed as\u0026nbsp;odds ratios (OR)\u0026nbsp;and 95% confidence intervals (CI) [18]. Longitudinal data from 2011 and 2015 were analyzed using logistic regression models to explore the relationship between headache and frailty. Four different models with various combinations of covariates were utilized. Specifically, Model 1 included only headache; Model 2 included age, gender, nation, hural and marital status; Model 3 further included education, ever/current smoke, ever/current alcohol, BMI and insurance; Model 4 further included hobby, nighttime sleep duration and co-morbidities [18].\u003c/p\u003e\n\u003cp\u003eWe employed logistic regression analysis (model 4) to perform subgroup analyses on the baseline (2011) and follow-up (2015) datasets [18]. The baseline analysis incorporated gender, age (with a cutoff of 60 years old), marital status, and BMI (with a cutoff of 25 kg/m\u0026sup2;) as categorical variables.\u0026nbsp;In the 2015 dataset analysis, building upon the aforementioned subgroups, we further incorporated the frailty status of non-frail individuals into the subgroup analyses. For these participants, health status was defined as FI\u0026le;10, while pre-frailty was defined as 10\u0026lt; FI \u0026lt; 32. The aim was to evaluate the influence of these variables on the headache-frailty association within defined subgroups.\u003c/p\u003e\n\u003cp\u003eAll statistical analyses were conducted using R software (version 4.4.0; R Foundation for Statistical Computing; http://www.R-\u0026shy;proje ct.org) and Free Statistics software (version2.01; Beijing Free Clinical Medical Technology Co., Ltd)., with a significance level set at 0.05 for all tests [18].\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eTable 1\u0026nbsp;\u003c/strong\u003epresents the baseline characteristics of the non-headache group (n = 10,314) and headache group (n = 1,416) at baseline (Wave 1,2011). Significant differences were observed between the groups. The headache group comprised a higher proportion of females (67.4% vs. 47.4%), fewer participants of Han ethnicity 91.7% vs. 92.6%), fewer individuals with a high school education or higher (0.4% vs. 2.6%), and a higher proportion of rural residents (71.1% vs. 55.9%)(all P \u0026lt; 0.001). Regarding lifestyle factors, the headache group reported lower engagement in hobbies (19.4% vs. 28.5%), as well as lower rates of ever/current smoking (30.5% vs. 42.3%) and drinking (32.8% vs. 41.9%). Comorbidity rates were higher in the headache group, including dyslipidemia (13.3% vs. 9.9%), liver disease (5.4% vs. 3.2%), kidney disease (12.7% vs. 4.5%), digestive diseases (38.2% vs. 18.8%), and frailty (30.2% vs. 7.8). Additionally, the headache group exhibited shorter sleep duration (5.7\u0026nbsp;\u0026plusmn;\u0026nbsp;2.1 vs. 6.5\u0026nbsp;\u0026plusmn;\u0026nbsp;1.7 hours), a slightly lower BMI (23.1\u0026nbsp;\u0026plusmn;\u0026nbsp;3.8 vs. 23.5\u0026nbsp;\u0026plusmn;\u0026nbsp;3.8), and a higher frailty index (median [IQR] 19.5 [13.7, 27.1] vs. 9.2 [4.8, 14.7]). All reported differences were significant (all P \u0026lt; 0.001). No significant differences were identified between the groups in age, marital status, or insurance coverage (all P \u0026gt; 0.05).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2\u0026nbsp;\u003c/strong\u003epresents the results of logistic regression models assessing the association between headache and frailty in wave1. In the unadjusted model (Model 1), the odds of frailty were significantly higher in the headache group (OR 5.13, 95% CI 4.48\u0026ndash;5.87). After adjusting for sociodemographic factors (age, gender, nationality, rural status, and marital status) in Model 2, the association remained significant (OR 5.39, 95% CI 4.60\u0026ndash;6.32). Further adjustment for lifestyle and anthropometric variables (education, smoking, alcohol use, BMI, and insurance coverage) in Model 3 marginally increased the odds (OR 5.45, 95% CI 4.60\u0026ndash;6.47). In Model 4, which additionally controlled for hobbies, nighttime sleep duration, and comorbidities, the headache group continued to exhibit significantly higher odds of frailty (OR 4.22, 95% CI 3.52\u0026ndash;5.06). All models showed a significant association between headache and increased odds of frailty (all P \u0026lt; 0.001).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFigure 2\u0026nbsp;presents subgroup analyses based on Model 4 . The headache group had a significantly higher adjusted odds of frailty (OR 4.22, 95% CI 3.52\u0026ndash;5.06) than the non-headache group in the overall population. This association was significant in all age subgroups (\u0026lt;60 years: OR 4.34, 95% CI 3.43\u0026ndash;5.5;\u0026nbsp;\u0026ge;60 years: OR 4.68, 95% CI 3.71\u0026ndash;5.91), marital status subgroups (unmarried: OR 3.85, 95% CI 2.43\u0026ndash;6.13; married: OR 4.37, 95% CI 3.67\u0026ndash;5.19), and BMI subgroups (\u0026lt;25 kg/m\u0026sup2;: OR 4.54, 95% CI 3.68\u0026ndash;5.59;\u0026nbsp;\u0026ge;25 kg/m\u0026sup2;: OR 4.47, 95% CI 3.29\u0026ndash;6.05). The association was also significant for those with headache and \u0026lt;6 hours of sleep (OR 3.48, 95% CI 2.75\u0026ndash;4.4) compared to those with\u0026nbsp;\u0026ge;6 hours (OR 4.2, 95% CI 3.35\u0026ndash;5.27). While the association strength varied by gender (females: OR 3.65, 95% CI 3\u0026ndash;4.45; males: OR 5.01, 95% CI 3.78\u0026ndash;6.63).No significant interactions were observed between headache and these subgroups. (all P-interaction \u0026ge; 0.05).\u003c/p\u003e\n\u003cp\u003eTable 3 presents the results of logistic regression models assessing the association between headache and frailty in wave 3.\u0026nbsp;In the unadjusted model (Model 1), the odds of frailty were significantly higher for individuals with episodic headache (OR 3.71, 95% CI 3.04\u0026ndash;4.53) and chronic headache (OR 8.30, 95% CI 5.91\u0026ndash;11.66). After adjusting for baseline sociodemographic factors (age, gender, nation, rural status, and marital status) in Model 2, the association remained significantly elevated for both incident (OR 3.49, 95% CI 2.73\u0026ndash;4.45) and chronic headache (OR 7.98, 95% CI 5.18\u0026ndash;12.28). Further adjustment for lifestyle factors, BMI, and insurance coverage in Model 3 slightly increased the odds for episodic headache (OR 3.71, 95% CI 2.93\u0026ndash;4.70) and maintained a significant association for chronic headache (OR 8.70, 95% CI 5.75\u0026ndash;13.16). In Model 4, which additionally controlled for hobbies, nighttime sleep duration, and comorbidities, both incident (OR 3.45, 95% CI 2.71\u0026ndash;4.41) and chronic headache remained significantly associated with frailty. All models showed a significant association between headache (both incident and chronic) and increased odds of frailty (all P \u0026lt; 0.001).\u003c/p\u003e\n\u003cp\u003eFigure 3 shows subgroup analyses based on Table 3 Model 4. Comparing to the non-headache group, individuals with chronic headache had a significantly higher adjusted odds of frailty (OR 7.95, 95% CI 5.16\u0026ndash;12.26), as did those with episodic headache (OR 3.45, 95% CI 2.71\u0026ndash;4.41). In age subgroups, both chronic (\u0026lt;60 years: OR 10.42, 95% CI 6.45\u0026ndash;16.83; \u0026ge;60 years: OR 7.88, 95% CI 3.91\u0026ndash;15.89) and episodic headache (\u0026lt;60 years: OR 3.71, 95% CI 2.72\u0026ndash;5.06; \u0026ge;60 years: OR 3.75, 95% CI 2.67\u0026ndash;5.26) were associated with higher odds of frailty. By gender, females with chronic headache had an OR of 7.23 (95% CI 4.68\u0026ndash;11.18) and males 8.59 (95% CI 3.69\u0026ndash;20.02), while females with episodic headache had an OR of 2.81 (95% CI 2.13\u0026ndash;3.71) and males 4.15 (95% CI 2.84\u0026ndash;6.06). In the marital status subgroup, both unmarried (OR 13.31, 95% CI 2.42\u0026ndash;73.06) and married (OR 8.68, 95% CI 5.82\u0026ndash;12.93) individuals with chronic headache had higher odds of frailty than the non-headache group. For episodic headache, unmarried individuals had an OR of 2.53 (95% CI 1.30\u0026ndash;4.92) and married individuals 3.61 (95% CI 2.84\u0026ndash;4.58). For BMI groups, chronic headache was associated with higher odds in both \u0026lt;25 kg/m\u0026sup2; (OR 9.71, 95% CI 6.03\u0026ndash;15.65) and \u0026ge;25 kg/m\u0026sup2; (OR 3.58, 95% CI 1.58\u0026ndash;8.07) subgroups. Episodic headache also showed elevated odds in both BMI subgroups (\u0026lt;25 kg/m\u0026sup2; OR 3.36, 95% CI 2.49\u0026ndash;4.55; \u0026ge;25 kg/m\u0026sup2; OR 3.48, 95% CI 2.39\u0026ndash;5.07). Regarding nighttime sleep duration, chronic headache had higher odds in both \u0026lt;6 hours (OR 6.80, 95% CI 3.76\u0026ndash;12.32) and \u0026ge;6 hours (OR 8.42, 95% CI 5.03\u0026ndash;14.12) subgroups. Episodic headache had elevated odds in the \u0026lt;6 hours subgroup (OR 2.92, 95% CI 2.00\u0026ndash;4.27) and slightly lower in the \u0026ge;6 hours subgroup (OR 3.52, 95% CI 2.67\u0026ndash;4.65). In the frailty group subgroup, chronic headache in the pre-frailty group had an OR of 8.30 (95% CI 2.47\u0026ndash;27.92) compared to the healthy group, while episodic headache had an OR of 2.29 (95% CI 1.13\u0026ndash;4.63). In the healthy group, episodic headache had an OR of 2.32 (95% CI 1.82\u0026ndash;2.96) and chronic headache 4.71 (95% CI 3.12\u0026ndash;7.10). Notably, no significant interactions were observed across any of the subgroups.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eAccording to our cross-sectional study, the incidence of frailty was significantly higher in individuals with headache than those without headache, and in our longitudinal study, individuals with episodic and chronic headache had a higher risk of developing frailty compared to those without headache. Subgroup analyses confirmed consistent associations across various demographics, including age and marital status. No significant interactions were noted across subgroups.\u003c/p\u003e\u003cp\u003eWith the exponential growth of the global aging population, frailty has become a prevalent health concern. Extensive research has established a significant association between frailty and pain. Chronic pain has been shown to have a robust positive correlation with frailty [\u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Empirical studies have demonstrated that approximately 40\u0026ndash;50% of frail elderly individuals concurrently experience chronic pain [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Elderly individuals with chronic pain are at a higher risk of developing frailty compared to those without chronic pain. In a longitudinal cohort study with an 8-year follow-up, pain alone was found to contribute to a substantial proportion of frailty cases compared to pain-free individuals [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Blyth et al. were the first to report that individuals meeting\u0026thinsp;\u0026ge;\u0026thinsp;3 frailty phenotype criteria are more likely to report pain [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Furthermore, frailty has been identified as an independent predictor of both acute and chronic postoperative pain (APSP and CPSP) following total knee arthroplasty (TKA) in older patients [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], and frail individuals are at a higher risk of developing chronic pain following cardiac surgery [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Similarly, a U-shaped relationship has been observed between the Frailty Index (FI) and the prevalence of low back pain (LBP) among middle-aged and older adults in China, indicating that both extremely low and high levels of frailty are associated with an increased risk of LBP [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. In hospitalized cancer patients, the FI has been shown to correlate with the presence and intensity of persistent pain [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Additionally, frailty is associated with more severe pain trajectories; frail individuals are 5\u0026ndash;6 times more likely than robust individuals to experience severe or very severe pain trajectories over a 9-year follow-up [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Further longitudinal studies have confirmed the bidirectional relationship between frailty and pain [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Collectively, these studies suggest a bidirectional relationship between pain and frailty, where in pain predicts the development of frailty, and frailty predicts the development or exacerbation of pain.\u003c/p\u003e\u003cp\u003eHowever, no studies discuss the relationship between headache and frailty. As primary headache affects approximately 50\u0026ndash;75% of adults globally [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], it is of vital importance to explore the relationship between headache and frailty. In this study, the incidence of frailty was significantly higher in individuals with headache than those without headache, and in our longitudinal study, individuals with episodic and chronic headache had a higher risk of frailty compared to those without headache. To our knowledge, this study is the first to investigate the association between headache and frailty.\u003c/p\u003e\u003cp\u003eThe pathophysiological mechanisms underlying the pain-frailty association may also explain the relationship between headache and frailty. First, chronic pain contributes to reduced mobility, lower resting metabolic rate, and diminished nutritional intake, all of which are hallmarks of frailty. Second, sustained pain activates the hypothalamic-pituitary-adrenal (HPA) axis, leading to hypercortisolemia [\u003cspan additionalcitationids=\"CR32\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e], a known contributor to frailty development. Third, pro-inflammatory signaling and immune dysregulation mediate the bidirectional relationship between chronic pain and frailty [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Furthermore, persistent pain may induce neurostructural changes, including gray matter atrophy and white matter tract degeneration, potentially impairing neural network efficiency [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. The mechanisms underlying headache and frailty calls for further exploration.\u003c/p\u003e\u003cp\u003eThis study possesses several methodological strengths. First, utilizing nationally representative data from the China Health and Retirement Longitudinal Study (CHARLS), it enabled a robust assessment of the association between headache and frailty in the aging Chinese population. Second, the large sample size surpassed those of prior comparable studies, enhancing statistical power. Third, the combined cross-sectional and longitudinal analyses strengthened the evidence for this association.\u003c/p\u003e\u003cp\u003eHowever, several limitations should be acknowledged. The retrospective design limited comprehensive adjustment for potential confounders. Additionally, a substantial proportion of CHARLS data contained missing or incomplete entries, which may have introduced bias. Furthermore, diagnoses within CHARLS primarily relied on self-reported questionnaires, potentially leading to recall bias and misclassification (e.g., undiagnosed cases categorized as healthy). Future prospective cohort studies are needed to better elucidate the temporal relationship between headache progression and frailty.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn this nationwide cohort study, we demonstrated that both incident and chronic headache were significantly associated with higher prevalence of frailty. Notably, headache sufferers exhibited elevated risks of developing pre-frailty and frailty states in the middle-aged and elderly Chinese population. Given that headache disorders may potentially contribute to the pathogenesis of frailty, effective headache management could serve as a crucial intervention for frailty prevention. This dual approach would not only enhance quality of life in aging populations but also alleviate the socioeconomic burden associated with geriatric care.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe CHARLS survey project received ethical approval from the Biomedical Ethics Committee of Peking University（IRB00001052-11015）\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used during the current study are available from the CHARLS database.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTJL and LXL analyzed and interpreted the data of the CHARLS.\u0026nbsp;CWL and KW made the tables and figures of the manuscript. HYX wrote the outline of the manuscript. BS analyzed the data and wrote the manuscript. CDW checked the manuscript, the tables and figures.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study available from the corresponding author on reasonable request.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank the researchers of the CHARLS database for providing public data for the research.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eClegg A, Young J, Iliffe S, Rikkert MO, Rockwood K. Frailty in elderly people. Lancet. 2013;381(9874):752-762. https://doi.org/10.1016/S0140-6736(12)62167-0.\u003c/li\u003e\n \u003cli\u003eRobertson DA, Savva GM, Kenny RA. Frailty and cognitive impairment: a review of the evidence and causal mechanisms. Ageing Res Rev. 2013;12(4):840-851. https://doi.org/10.1016/j.arr.2013.06.002.\u003c/li\u003e\n \u003cli\u003eCesari M, Calvani R, Marzetti E. Frailty in older persons. Clin Geriatr Med. 2017;33(2):293-303. https://doi.org/10.1016/j.cger.2017.02.002IF: 3.1 Q3 .\u003c/li\u003e\n \u003cli\u003eFried LP, Tangen CM, Walston J, et al. Frailty in older adults: evidence for a phenotype. J Gerontol A Biol Sci Med Sci. 2001;56(3):M146-M156. https://doi.org/10.1093/gerona/56.3.m146.\u003c/li\u003e\n \u003cli\u003eSearle SD, Mitnitski A, Gahbauer EA, Gill TM, Rockwood K. A standard procedure for creating a frailty index. BMC Geriatr. 2008;8(1):24. https://doi.org/10.1186/1471-2318-8-24.\u003c/li\u003e\n \u003cli\u003eGBD 2016 Neurology Collaborators. Global, regional, and national burden of neurological disorders, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet Neurol. 2019;18(4):459-480. https://doi.org/10.1016/S1474-4422(19)30016-9.\u003c/li\u003e\n \u003cli\u003eGiamberardino MA, Affaitati G, Costantini R, Guglielmetti M, Martelletti P. Acute headache management in emergency department: a narrative review. Intern Emerg Med. 2020;15(1):109-117. https://doi.org/10.1007/s10194-019-01042-z.\u003c/li\u003e\n \u003cli\u003eSteiner TJ, Stovner LJ, Chowdhury DI, et al. Migraine remains second among the world\u0026rsquo;s causes of disability, and first among young women: findings from GBD2019. J Headache Pain. 2020;21(1):137. https://doi.org/10.1186/s10194-020-01208-0.\u003c/li\u003e\n \u003cli\u003eVetvik KG, MacGregor EA. Sex differences in the epidemiology, clinical features, and pathophysiology of migraine. Lancet Neurol. 2017;16(1):76-87. https://doi.org/10.1016/S1474-4422(16)30293-9.\u003c/li\u003e\n \u003cli\u003eWang MH, Pan LJ, Zhang YH, et al. Prevalence and risk factors of headache in Chinese with stroke: a cross-sectional study based on CHARLS. J Headache Pain. 2024;25(1):1-10. https://doi.org/10.1186/s10194-024-01930-z.\u003c/li\u003e\n \u003cli\u003eMin D, Anle D, Lijie Z, Xiaoyun X. The impact of diabetes on chronic pain in different body regions among adults aged 50 and older: a cross-sectional analysis. Front Public Health. 2025;13:0. https://doi.org/10.3389/fpubh.2025.1520735.\u003c/li\u003e\n \u003cli\u003eLiu HX, Zhang SH, Gong ZH, et al. Association between migraine and cardiovascular disease mortality: A prospective population-based cohort study. Headache. 2023 Sep;63(8):1109-1118. https://doi.org/10.1111/head.14616.\u003c/li\u003e\n \u003cli\u003eLi TJ, Li LX, Xie HY, et al. Association between chronic pain and cognitive frailty among middle-aged and elderly individuals: evidence from the China Health and Retirement Longitudinal Study. Front Aging Neurosci. 2024;16:0. https://doi.org/10.3389/fnagi.2024.1491120.\u003c/li\u003e\n \u003cli\u003eChen JT, Yan LY, Chu JJ, Wang XY, Xu ZR. Pain Characteristics and Progression to Sarcopenia in Chinese Middle-Aged and Older Adults: A 4-Year Longitudinal Study. J Gerontol A Biol Sci Med Sci. 2024;79(5):1-10. https://doi.org/10.1093/gerona/glae080.\u003c/li\u003e\n \u003cli\u003eXie X, Que J, Sun L, et al. Association between urbanization levels and frailty among middle-aged and older adults in China: evidence from the CHARLS. BMC Medicine. 2025;23(1):0-0. https://doi.org/10.1186/s12916-025-03961-y.\u003c/li\u003e\n \u003cli\u003eHe D, Qiu YW, Yan MS, et al. Associations of metabolic heterogeneity of obesity with frailty progression: Results from two prospective cohorts. J Cachexia Sarcopenia Muscle. 2023;14(1):632-641. https://doi.org/10.1002/jcsm.13169.\u003c/li\u003e\n \u003cli\u003eMak HW, Noguchi T, Bone JK, et al. Hobby engagement and mental wellbeing among people aged 65 years and older in 16 countries. Nat Med. 2023;29(8):2233-2240. https://doi.org/10.1038/s41591-023-02506-1.\u003c/li\u003e\n \u003cli\u003eTianjiao\u0026nbsp;Li, Lingxuan\u0026nbsp;Li, Hongyang\u0026nbsp;Xie, Rongyu\u0026nbsp;Ping, Yane\u0026nbsp;Guo, Dongmei\u0026nbsp;Li, Yuwei\u0026nbsp;Zhang, Xiujuan\u0026nbsp;Bai and Bo\u0026nbsp;Sun. Association between chronic pain and cognitive frailty among middle-aged and elderly individuals: evidence from the China Health and Retirement Longitudinal Study. Frontiers in Aging Neuroscience. 10.3389/fnagi.2024.1491120.\u003c/li\u003e\n \u003cli\u003eBlyth FM, Rochat S, Cumming RG, et al. Pain, frailty and comorbidity in older men: The CHAMP study. Pain. 2008;140(1):224-230. https://doi.org/10.1016/j.pain.2008.08.011.\u003c/li\u003e\n \u003cli\u003eCoelho T, Paul C, Gobbens RJJ, Fernandes L. Multidimensional frailty and pain in community-dwelling elderly. Pain Med. 2017;18(4):693-701. https://doi.org/10.1111/pme.12746.\u003c/li\u003e\n \u003cli\u003eWade KF, Marshall A, Vanhoutte B, et al. Does pain predict frailty in older men and women? Findings from the English Longitudinal Study of Ageing (ELSA). J Gerontol A Biol Sci Med Sci. 2017;72(3):403-409. https://doi.org/10.1093/gerona/glw226.\u003c/li\u003e\n \u003cli\u003eChang CI, Chan DC, Kuo KN, Hsiung CA, Chen CY. Prevalence and correlates of geriatric frailty in a northern Taiwan community. J Formos Med Assoc. 2011;110(4):247-257. https://doi.org/10.1016/S0929-6646(11)60037-5.\u003c/li\u003e\n \u003cli\u003eShega JW, Andrew M, Kotwal A, et al. Relationship between persistent pain and 5-year mortality: A population-based prospective cohort study. J Am Geriatr Soc. 2013;61(12):2135-2141. https://doi.org/10.1111/jgs.12554.\u003c/li\u003e\n \u003cli\u003eBlyth FM, Rochat S, Cumming RG, et al. Pain, frailty and comorbidity in older men: the CHAMP study. Pain. 2008;140(1):224-230. https://doi.org/10.1016/j.pain.2008.08.011.\u003c/li\u003e\n \u003cli\u003eJin Y, Tang S, Wang W, et al. Preoperative frailty predicts postoperative pain after total knee arthroplasty in older patients: a prospective observational study. Eur Geriatr Med. 2024;15(3):657-665. https://doi.org/10.1007/s41999-024-00932-z.\u003c/li\u003e\n \u003cli\u003eArends BC, Timmerman L, Vernooij LM, et al. Preoperative frailty and chronic pain after cardiac surgery: a prospective observational study. BMC Anesthesiol. 2022;22(1):201. https://doi.org/10.1186/s12871-022-01746-x.\u003c/li\u003e\n \u003cli\u003eQing L, Zhu Y, Feng L, et al. Exploring the association between Frailty index and low back pain in middle-aged and older Chinese adults: a cross-sectional analysis of data from the China Health and Retirement Longitudinal Study (CHARLS). BMJ Open. 2024;14(3):e085645. https://doi.org/10.1136/bmjopen-2024-085645.\u003c/li\u003e\n \u003cli\u003eCrosignani S, Orlandini L, Baruffi S, et al. Frailty and persistent pain in oncological patients undergoing rehabilitation. J Frailty Aging. 2022;11(3):286-290. https://doi.org/10.14283/jfa.2022.26.\u003c/li\u003e\n \u003cli\u003eCai G, Zhang Y, Wang Y, et al. Frailty predicts knee pain trajectory over 9 years: results from the osteoarthritis initiative. Pain Med. 2023;24(6):1364-1371. https://doi.org/10.1093/pm/pnad097.\u003c/li\u003e\n \u003cli\u003eChaplin WJ, McWilliams DF, Millar BS, et al. The bidirectional relationship between chronic joint pain and frailty: data from the investigating musculoskeletal health and wellbeing cohort. BMC Geriatr. 2023;23(1):273. https://doi.org/10.1186/s12877-023-03949-4.\u003c/li\u003e\n \u003cli\u003eMcBeth J, Chiu YH, Silman AJ, et al. Hypothalamic-pituitary-adrenal stress axis function and the relationship with chronic widespread pain and its antecedents. Arthritis Res Ther. 2005;7(5):R992-R1000. https://doi.org/10.1186/ar1826.\u003c/li\u003e\n \u003cli\u003eChoi C-J, Knudsen R, Oda K, et al. The association between incident self-reported fibromyalgia and nonpsychiatric factors: 25 years follow-up of the Adventist Health Study. J Pain. 2010;62(6):611-617. https://doi.org/10.1016/j.jpain.2010.03.002.\u003c/li\u003e\n \u003cli\u003eVaradhan R, Walston J, Cappola AR, et al. Higher levels and blunted diurnal variation of cortisol in frail older women. J Gerontol A Biol Sci Med Sci. 2008;63(2):190-195. https://doi.org/10.1093/gerona/63.2.190.\u003c/li\u003e\n \u003cli\u003eEdwards RR, Kronfli T, Haythornthwaite JA, et al. Association of catastrophizing with interleukin-6 responses to acute pain. Pain. 2008;140(1):135-144. https://doi.org/10.1016/j.pain.2008.07.003.\u003c/li\u003e\n \u003cli\u003eMalfliet A, Coppieters I, Van Wilgen P, et al. Brain changes associated with cognitive and emotional factors in chronic pain: a systematic review. Eur J Pain. 2017;21(3):769-786. https://doi.org/10.1002/ejp.978.\u003c/li\u003e\n \u003cli\u003eGomez-Beldarrain M, Oroz I, Zapirain BG, et al. Right fronto-insular white matter tracts link cognitive reserve and pain in migraine patients. J Headache Pain. 2016;17(1):4. https://doi.org/10.1186/s10194-016-0600-9.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable1 Baseline characteristics of study population in wave 1\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"571\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eTotal (n = 11730)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003eNon-headache(n = 10314)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003eHeadache(n = 1416)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003eP \u0026nbsp;value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003eAge(years, M \u0026plusmn; SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e58.3\u0026nbsp;\u0026plusmn;\u0026nbsp;9.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e58.4\u0026nbsp;\u0026plusmn;\u0026nbsp;9.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e58.1\u0026nbsp;\u0026plusmn;\u0026nbsp;8.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e0.234\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003eGender, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Female\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e5839 (49.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e4885 (47.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e954 (67.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Male\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e5891 (50.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e5429 (52.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e462 (32.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003eMarital, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e0.075\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Married\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e1287 (11.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e1112 (10.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e175 (12.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Unmarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e10443 (89.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e9202 (89.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e1241 (87.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003eEthnic group , n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e712 ( 7.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e615 (7.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e97 (8.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003eHan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e8735 (92.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e7657 (92.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e1078 (91.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003eEducation, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003eBelow high school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e10085 (86.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e8755 (84.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e1330 (93.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003eHigh school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e1370 (11.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e1289 (12.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e81 (5.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003eCollege or above\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e275 ( 2.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e270 (2.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e5 (0.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003eResidence , n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e4954 (42.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e4545 (44.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e409 (28.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e6776 (57.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e5769 (55.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e1007 (71.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003eHobby, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e8516 (72.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e7375 (71.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e1141 (80.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e3213 (27.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e2938 (28.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e275 (19.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003eEver/current smoke, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e6931 (59.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e5947 (57.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e984 (69.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e4798 (40.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e4366 (42.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e432 (30.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003eEver/current drink, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e6944 (59.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e5993 (58.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e951 (67.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e4783 (40.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e4318 (41.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e465 (32.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003eInsurance, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e0.458\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e714 ( 6.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e634 (6.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e80 (5.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e10981 (93.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e9648 (93.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e1333 (94.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003eComorbidities\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003eDyslipidemia, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e10430 (89.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e9214 (90.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e1216 (86.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e1199 (10.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e1012 (9.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e187 (13.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003eLiverDisease, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e11311 (96.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e9977 (96.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e1334 (94.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e402 ( 3.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e326 (3.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e76 (5.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003eKidneyDisease, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e11068 (94.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e9836 (95.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e1232 (87.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e639 ( 5.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e459 (4.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e180 (12.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003eDigestiveDisease, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e9241 (78.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e8369 (81.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e872 (61.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e2480 (21.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e1940 (18.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e540 (38.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003eFrailty, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e10502 (89.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e9513 (92.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e989 (69.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e1228 (10.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e801 (7.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e427 (30.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003eNighttime sleep duration, M \u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e6.4\u0026nbsp;\u0026plusmn;\u0026nbsp;1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e6.5\u0026nbsp;\u0026plusmn;\u0026nbsp;1.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e5.7\u0026nbsp;\u0026plusmn;\u0026nbsp;2.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003eBMI, M \u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e23.5 \u0026plusmn; 3.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e23.5 \u0026plusmn; 3.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e23.1 \u0026plusmn; 3.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 197px;\"\u003e\n \u003cp\u003eFrailty Index,Median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e10.7 (5.1, 17.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e9.2 (4.8, 14.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e19.5 (13.7, 27.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviations: BMI, body mass index; M\u0026plusmn; SD, mean \u0026plusmn; standard deviation. IQR, interquartile range.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eT\u003c/strong\u003e\u003cstrong\u003eable2 Logistic\u0026nbsp;regression model on headache and frailty in wave 1\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"570\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 51px;\"\u003e\n \u003cp\u003eHeadache\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 380px;\"\u003e\n \u003cp\u003eModel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 121px;\"\u003e\n \u003cp\u003eModel1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003eModel2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003eModel3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003eModel4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eOR (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eOR(95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003eOR(95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003eOR(95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51px;\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 51px;\"\u003e\n \u003cp\u003eNon-headache\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e1(Ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e1(Ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e1(Ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e1(Ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 51px;\"\u003e\n \u003cp\u003eHeadache\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e5.13 (4.48~5.87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e5.39 (4.6~6.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e5.45 (4.6~6.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e4.22 (3.52~5.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eNotes:\u003c/strong\u003e \u003cstrong\u003eModel 1:\u003c/strong\u003e No adjustment; \u003cstrong\u003eModel 2:\u003c/strong\u003e Adjusted for age, gender, ethnic group, hural and marital status; \u003cstrong\u003eModel 3:\u0026nbsp;\u003c/strong\u003eModel 2 + education,ever/current smoke,ever/current alcohol,BMI, insurance; Model 4: Model 3 +hobby,Nighttime sleep duration, Comorbidities\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eT\u003c/strong\u003e\u003cstrong\u003eable3 Logistic\u0026nbsp;regression model on Headache and Frailty at 2015\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"570\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 51px;\"\u003e\n \u003cp\u003eHeadache\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 380px;\"\u003e\n \u003cp\u003eModel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003eModel1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 130px;\"\u003e\n \u003cp\u003eModel2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003eModel3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003eModel4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eOR (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eOR(95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003eOR(95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003eOR(95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51px;\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 51px;\"\u003e\n \u003cp\u003eNon-headache\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e1(Ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e1(Ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e1(Ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e1(Ref)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 51px;\"\u003e\n \u003cp\u003eEpisodic Headache\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e3.71 (3.04~4.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e3.49 (2.73~4.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e3.71 (2.93~4.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e3.45 (2.71~4.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 51px;\"\u003e\n \u003cp\u003eChronic\u003c/p\u003e\n \u003cp\u003eHeadache\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e8.3 (5.91~11.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e7.98 (5.18~12.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e8.70 (5.75~13.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e7.95 (5.16~12.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eNotes:\u003c/strong\u003e \u003cstrong\u003eModel 1:\u003c/strong\u003e No adjustment; \u003cstrong\u003eModel 2:\u003c/strong\u003e Adjusted for age, gender, ethnic group, hural and marital status; \u003cstrong\u003eModel 3:\u0026nbsp;\u003c/strong\u003eModel 2 + education,ever/current smoke,ever/current alcohol,BMI,insurance; Model 4: Model 3 +hobby,Nighttime sleep duration, Comorbidities\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Headache, Frailty, Middle-aged and elderly population, China Health and Retirement Longitudinal Study (CHARLS)","lastPublishedDoi":"10.21203/rs.3.rs-6935511/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6935511/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003eFrailty, a clinically recognized geriatric syndrome marked by diminished physiological reserve and heightened vulnerability to adverse health outcomes stemming from multisystem dysregulation, represents a growing global health challenge. This investigation sought to examine the potential association between cephalalgia and incident frailty risk in aging populations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eLeveraging longitudinal data from the China Health and Retirement Longitudinal Study (CHARLS) across 2011-2015 waves, we performed both cross-sectional and prospective cohort analyses involving 17,705 community-dwelling adults aged ≥45 years. Episodic headache was defined as reporting headache either at baseline (2011, Wave 1) or at the follow-up (2015, Wave 3).Chronic headache was defined as reporting headache at both baseline (2011, Wave 1) and at the follow-up endpoint (2015, Wave 3).. Frailty status was quantified using a validated 32-item frailty index (FI) encompassing functional, cognitive, and comorbid conditions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e \u0026nbsp;At Wave 1, significant differences were observed between the headache group (n = 1,416) and non-headache group (n = 10,314). The headache group had a higher proportion of females (67.4% vs. 47.4%) and a higher prevalence of comorbidities, including frailty (30.2% vs. 7.8%). They also reported lower engagement in hobbies, smoking, and drinking, as well as shorter sleep duration (5.7 ± 2.1 vs. 6.5 ± 1.7 hours) (all P \u0026lt; 0.001). Logistic regression analysis indicated significantly higher odds of frailty for the headache group in the unadjusted model (OR 5.13, 95% CI 4.48–5.87) and after adjusting for sociodemographic factors (OR 5.39, 95% CI 4.60–6.32) and lifestyle factors (OR 4.22, 95% CI 3.52–5.06) (all P \u0026lt; 0.001).\u003c/p\u003e\n\u003cp\u003eAt Wave 3, individuals with chronic headache had markedly elevated odds of frailty (OR 8.30, 95% CI 5.91–11.66) compared to episodic headache (OR 3.71, 95% CI 3.04–4.53). Both chronic (OR 7.98, 95% CI 5.18–12.28) and episodic headaches (OR 3.49, 95% CI 2.73–4.45) remained significantly associated with frailty after adjustments. Subgroup analyses confirmed consistent associations across various demographics, including age and marital status (all P \u0026lt; 0.001). No significant interactions were noted across subgroups.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003eOur study demonstrates that headache is significantly associated with an increased risk of frailty in middle-aged and older adults, with chronic headache showing a more pronounced effect. These results underscore the clinical imperative for optimized headache management strategies as a potential modifiable factor in frailty prevention. Implementing such strategies may concurrently improve geriatric quality of life and reduce the socioeconomic burdens linked to aging-related disability.\u003c/p\u003e","manuscriptTitle":"Association between Headache and Frailty among Middle-aged and Elderly Individuals: Evidence from the China Health and Retirement Longitudinal Study (CHARLS)","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-13 14:13:48","doi":"10.21203/rs.3.rs-6935511/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b059d65f-b85b-4387-86dc-2184e00b8e52","owner":[],"postedDate":"August 13th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":52923155,"name":"Health sciences/Health care"},{"id":52923156,"name":"Health sciences/Neurology"}],"tags":[],"updatedAt":"2025-08-19T06:38:26+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-13 14:13:48","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6935511","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6935511","identity":"rs-6935511","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}