Childbirth History Increases Arthritis Risk in Women: The Role of Lipid Metabolism and Physical Activity

Childbirth History Increases Arthritis Risk in Women: The Role of Lipid Metabolism and Physical Activity | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Childbirth History Increases Arthritis Risk in Women: The Role of Lipid Metabolism and Physical Activity Huiyan Wang, Ming Zhang, Bin Yu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6597672/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 OBJECTIVE To investigate the association between childbirth and arthritis, with a focus on the mediating effect of blood lipid indexes and protective role of physical Activity. METHODS The cross-sectional study utilized data from the National Health and Nutrition Examination Survey (NHANES) from 2007 to 2020. Blood lipid indexes were included triglyceride, total cholesterol (TC), LDL-cholesterol (LDL-C) and HDL-cholesterol (HDL-C, mmol/L). Then, remnant cholesterol (RC) was calculated. RESULTS A total of 6491 participants were included in this study, 2144 (33.03%) women occurred arthritis. Compared to never pregnancy women, the rates of arthritis in the participants with had childbirth were significantly increase (36.03% vs 17.94%, p < 0.001). After adjusted, the risk of arthritis for the women had childbirth was significantly increased (OR = 4.17, p < 0.0001). In addition, the birth number and birth interval cycle would increase the risk of arthritis caused by childbirth experience. There was a nonlinear (L-shaped) relationship were observed in blood triglyceride and RC (p for nonlinearity < .001). Mediation analysis demonstrated that blood RC accounted for 8.45% of observed association between childbirth and arthritis (p < 0.001). RC was the highest WQS weigh among four cholesterols, with the highest contributions 0.63. There was a nonlinear (U-shaped) relationship between vigorous recreational activities and the risk of arthritis (p for nonlinearity < 0.001). CONCLUSIONS Childbirth history is a significant yet underrecognized risk factor for arthritis in women, mediated in part by persistent lipid abnormalities, particularly elevated RC, while physical activity offers protective benefits. childbirth pregnancy arthritis lipid cholesterol physical activity Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Highlights The first large-scale epidemiological investigation systematically evaluated the relationship between childbirth and arthritis risk in women, with a focus on elucidating the mediating role of blood lipid indexes (particularly remnant cholesterol) and the protective effects of physical activity. Childbirth is independently associated with a 2.21~4.17-fold increased risk of arthritis in women. Elevated blood remnant cholesterol levels mediate approximately 8.45% of this association, exhibiting a nonlinear threshold effect. There was a nonlinear (U-shaped) relationship between vigorous recreational activities and the risk of arthritis (p for nonlinearity <0.001), and an inflection point (35 minutes on a typical day) was found. Introduction Arthritis is one of the most prevalent chronic conditions in the world and the most prevalent chronic condition in women 1 , 2 . Osteoarthritis (OA) and rheumatoid arthritis (RA) are the most common forms, contributing to chronic pain, reduced mobility, and diminished quality of life. In addition, arthritis is one of the leading causes of disability and limitations in activities of daily living, and its economic, psychological, and social impact is enormous. Women exhibit unique risk profiles influenced by hormonal fluctuations 3 , 4 , genetic predisposition 5 , and lifestyle factors 6 . Despite advances in treatment, arthritis remains a major public health challenge, necessitating deeper insights into modifiable risk factors, particularly those linked to women’s life-course events. Pregnancy and childbirth are cardinal events in a woman's life course, exerting profound and enduring impacts on both short-term and long-term health 7 , including physiology, metabolism and psychology 8 . From a physiological perspective, pregnancy induces a cascade of adaptations across multiple organ systems, especially cardiovascular system 9 and endocrine system 2 , and so on. Beyond their immediate role in reproduction, these experiences are increasingly recognized for their dual impact on long-term health trajectories. Previous studies have predominantly focused on the adverse effects of pregnancy complications on women's health 10 , 11 . Recently, epidemiological evidence highlights potential protective effects of parity 12 – 15 . However, the relationship between reproductive history and arthritis remains unclear. Previous studies mainly focused on the pregnant risks and management of women with arthritis or rheumatoid diseases 16 . Existing literature on reproductive factors and arthritis risk is inconclusive. Pang et al 17 reported that there was no reliable causal relationship between age at menarche/age at menopause and OA, but an increase in age at first live birth and umber of live births was associated with an increased risk of OA. However, Ranjbaran’s group 18 didn’t find a significant correlation between RA and reproductive related indicators (including number of pregnancies, age at first pregnancy, duration of breastfeeding and number of children). It is well known that dyslipidemia is increasingly recognized as a contributor to arthritis pathogenesis 19 , 20 . Recent attention has turned to remnant cholesterol (RC) as a potent pro-inflammatory agent, and it can increase the risk of RA 21 . High-density lipoprotein cholesterol (HDL-C) exhibits paradoxical roles in arthritis. Choudhury reported that low HDL cholesterol levels were more common in RA patients 22 , but Giacaglia obtained the opposite result 23 . In addition, pregnancy imposes profound, lasting changes on lipid metabolism. During gestation, maternal cholesterol levels rise to support fetal neurodevelopment, and characterized by increases in both low-density lipoprotein cholesterol (LDL-C) and triglyceride levels 24 . Postpartum, these elevations often persist, particularly in women with gestational dyslipidemia or excessive weight retention 25 , 26 . Despite these insights, no study has systematically evaluated how reproductive timing, parity, and lipid alterations collectively influence arthritis. Furthermore, physical activity was considered cloud improve postpartum woman health without adversely impacting breast milk supply or quality, infant growth or maternal injury 27 . And it was also an effective method to reduce blood lipid 28 , 29 . Here, in order to explore the association between childbirth experience and risk of arthritis, we investigated seven cycles of the National Health and Nutrition Examination Survey (NHANES) 30 , 31 . We clarified their relationship firstly, and discussed the role of blood lipids (especially cholesterol). Then, we explored the improvement effect of physical activity. This study offers new insights into potential health risks associated with childbirth experience, and hope to contribute to improving public health outcomes. Materials and Methods Data source and study population The cross-sectional study was from seven cycles of NHANES (2007 ~ 2020). The participant’s selection is illustrated in Fig. 1 . Of 66148 initial subjects, 32793 were excluded due to male sex. 16627 were excluded due to incomplete data of age, education level, race, poverty ratio and body mass index (BMI). 9184 were excluded due to missing the data of blood lipid indexes.1053 were excluded due to missing the information of pregnancy, childbirth and arthritis. Finally, 6491 women were included in this study. According to their experience of pregnancy and childbirth, the subjects were divided into two groups: never pregnancy women (G1, n = 2144), and had childbirth (G2, n = 4347). Definition of pregnancy and childbirth history Pregnancy history was measured by the following question: “Ever been pregnant? (RHQ131)”, including current pregnancy, live births, miscarriages, stillbirths, tubal pregnancies and abortions. Women who answer yes were considered as having pregnancy. While the participants who answer no were considered as never pregnancy (G1). Similarly, childbirth history and birth number were defined according to the question: “How many deliveries live birth result? (RHQ171)”. Women who answer the number of live births more than one were considered as having childbirth (G2). Next, the definition of age at first birth (AFB) and age at last birth (ALB) were based on the Questionnaire Data of “Age at first live birth (RHQ180)” and “Age at last live birth (RHD190)” respectively. Birth interval cycle was calculated as ALB-AFB. Definition of arthritis Just as the previous study 32 , arthritis was measured by the following question (MCQ160a): Has a doctor or other health professional ever told you that you had arthritis? Women who answer yes were considered as have arthritis. Measurements of blood lipid indexes Women's blood lipid index in questionnaire were obtained from laboratory data, including triglyceride (mmol/L), total cholesterol (TC, mmol/L), LDL-cholesterol (LDL-C, mmol/L) and HDL-cholesterol (HDL-C, mmol/L). According to the study 33 , remnant cholesterol (RC) was calculated as deducting the levels of LDL-C and HDL-C from TC. According to the literature 34 , we convert the unit of sitting time in hours and divide it into four levels: Q1( = 0.88 mmol/L). Meanwhile, Q1 was defined as the reference in the follow-up study. Measurements of physical Activity Physical Activity were obtained from questionnaire data, including vigorous recreational activities (PAQ650) and moderate recreational activities (PAQ665). The time of their activities were extracted from PAD660 and PAD675 respectively, and the unit was minutes. Other covariates Similar to some other studies 35 , 36 , age, gender, race education level, race and poverty ratio were obtained from demographics data. BMI and weight were collected from examination data. Statistical Analysis DecisionLinnc1.0 software 37 was employed for data analysis, which is a platform that integrates multiple programming language environments. Logistic regression analysis model was employed to across three distinct models to examine the relationship between childbirth experience and arthritis. Subgroup analyses were also conducted. Next, restricted cubic splines (RCS) was utilized to explore potential non-linear relationships between blood lipid indexes and the risk of arthritis caused by childbirth experience. Weighted Quantile Sum (WQS) regression was used to explore the overall effect of blood lipid indexes. P < 0.05 was considered statistically significant. Results Baseline participant characteristics A total of 6491 participants with complete data from NHANES (2007 ~ 2020) were included in this study. As shown in Fig. 2 , the median (Q1 ~ Q3) of birth number was 3 (2 ~ 4) in the United States, and the number of births in 2020 significantly decreased compared with 2007 (p < 0.001). At the same time, in recent years, the age of last birth has become more younger (p = 0.006). However, there were no significant difference in age at fist birth (p = 0.821). Therefore, the birth interval cycle also showed a significant downward trend (p = 0.020). Table 1 presents the baseline characteristics of the participants according to childbirth history. Of 6491 participants, 2144 (33.03%) women occurred arthritis. Compared to never pregnancy women(G1), the prevalence of arthritis was significantly increased in the participants with childbirth experience (G2) (36.03% vs 17.94%, p < 0.001). At the same time, the women who had experience of childbirth showed abnormalities in several blood lipid indexes, which are characterized by a significant decrease in HDL-C and a significant increase in other indexes (triglyceride, TC, LDL-C and RC). In addition, they were also generally older (p < 0.001) and had higher BMI (p < 0.001). Table 1 Baseline participant characteristics according to birth history Variable Names Overall Childbirth history p-value G1 (no) G2 (yes) n 6491 1076 5415 Age (year) 50.109 ± 17.552 37.447 ± 17.376 52.625 ± 16.467 < 0.001 Race (%) < 0.001 Mexican American 924 (14.24) 116 (10.78) 808 (14.92) Other Hispanic 695 (10.71) 98 (9.11) 597 (11.02) Non-Hispanic White 2781 (42.84) 475 (44.14) 2306 (42.59) Non-Hispanic Black 1352 (20.83) 201 (18.68) 1151 (21.26) Other Race 739 (11.38) 186 (17.29) 553 (10.21) Poverty income ratio 2.429 ± 1.613 2.729 ± 1.677 2.369 ± 1.594 < 0.001 =5.0 1039 (16.01) 230 (21.38) 809 (14.94) Education level (%) < 0.001 Less than 9th grade 555 (8.55) 34 (3.16) 521 (9.62) 9-11th grade 857 (13.20) 50 (4.65) 807 (14.90) High school graduate 1410 (21.72) 167 (15.52) 1243 (22.95) Some college 2093 (32.24) 379 (35.22) 1714 (31.65) College graduate or above 1576 (24.28) 446 (41.45) 1130 (20.87) BMI (kg/m2) 29.809 ± 7.852 28.587 ± 9.032 30.052 ± 7.573 < 0.001 Normal weight (%) 1917 (29.53) 473 (43.96) 1444 (26.67) Overweight (%) 1836 (28.29) 238 (22.12) 1598 (29.51) Obesity (%) 2738 (42.18) 365 (33.92) 2373 (43.82) Triglyceride 109.138 ± 60.569 93.243 ± 53.481 112.297 ± 61.398 < 0.001 Total-cholesterol 5.002 ± 1.059 4.828 ± 1.006 5.036 ± 1.066 < 0.001 LDL-cholesterol 2.92 ± 0.918 2.794 ± 0.865 2.945 ± 0.926 < 0.001 HDL-cholesterol 1.517 ± 0.423 1.553 ± 0.421 1.51 ± 0.424 0.003 Remnant cholesterol 0.564 ± 0.314 0.482 ± 0.277 0.581 ± 0.318 < 0.001 Q1 2614 (40.27) 557 (51.77) 2057 (37.99) Q2 1632 (25.14) 256 (23.79) 1376 (25.41) Q3 1336 (20.58) 172 (15.99) 1164 (21.50) Q4 909 (14.00) 91 (8.46) 818 (15.11) Arthritis < 0.001 Without 4347 (66.97) 883 (82.06) 3464 (63.97) Had 2144 (33.03) 193 (17.94) 1951 (36.03) Table 2 compared the levels of blood lipid according to arthritis or reproductive-related indicators respectively. Notably, the levels of TC and RC were significantly increased in the women had arthritis (p 0.05). Meanwhile, the more birth number and the longer birth interval cycle, the higher the level of RC. Table 2 Comparison of cholesterol levels n TC (mmol/L) LDL-C (mmol/L) HDL-C (mmol/L) Remnant cholesterol (mmol/L) Arthritis Without 4347 4.951 ± 1.043 2.906 ± 0.901 1.512 ± 0.405 0.534 ± 0.303 Had 2144 5.104 ± 1.085 2.949 ± 0.95 1.528 ± 0.458 0.627 ± 0.324 p-value < 0.001 0.073 0.147 < 0.001 Birth number 1 1106 4.95 ± 1.07 2.887 ± 0.919 1.518 ± 0.417 0.545 ± 0.321 2 1790 5.084 ± 1.064 2.982 ± 0.935 1.53 ± 0.445 0.572 ± 0.311 3 1271 5.039 ± 1.067 2.951 ± 0.917 1.5 ± 0.403 0.589 ± 0.318 4 ~ 8 1173 5.044 ± 1.056 2.942 ± 0.919 1.487 ± 0.422 0.615 ± 0.319 >=8 75 5 ± 1.159 2.881 ± 1.029 1.452 ± 0.321 0.668 ± 0.348 p-value 0.028 0.105 0.038 < 0.001 Age at first birth =35 91 5.355 ± 1.233 3.206 ± 1.09 1.639 ± 0.502 0.511 ± 0.302 p-value 0.010 0.002 < 0.001 0.088 Age at last birth =35 959 5.133 ± 1.042 3.004 ± 0.904 1.541 ± 0.443 0.588 ± 0.32 p-value 0.002 0.002 0.003 0.711 Birth interval cycle =10 years 1206 5.061 ± 1.036 2.963 ± 0.899 1.479 ± 0.407 0.618 ± 0.325 p-value 0.597 0.121 0.004 < 0.001 Associations between childbirth experience and arthritis We have established three models before and after adjusting for confounding factors respectively. As shown in Table 3 , three models established a statistically significant association between childbirth experience and arthritis. In the unadjusted model (Model 1), the risk of arthritis for the women had childbirth was significantly increased. The odds ratio (OR) and 95% confidence intervals (CIs) was 2.58 (2.19, 3.05) (p < 0.0001). After additionally adjusting for general data confounding factors such as race, education, poverty income ratio, BMI (Model 2), childbirth experience was still associated with an increased risk of arthritis (OR = 2.21, p < 0.0001). Furthermore, model 3 still showed this trend of increasing risk after additionally adjusting for birth number, age at first birth, age at last birth and birth interval cycle (OR = 4.17, p < 0.0001). In addition, the birth number and birth interval cycle would increase the risk of arthritis caused by childbirth experience (Fig. 3 ). For example, compared with women who delivered one live birth, women who have more than three children had a significantly higher risk of arthritis. Meanwhile, if the birth interval exceeds 10 years, it would also significantly increase the risk. However, the woman of advanced maternal age didn’t increase the risk of arthritis, regardless of the age at first birth or age at last birth. Table 3 Multivariable-adjust ORs and 95%CI of birth history and accelerated aging Model 1 Model 2 Model 3 OR (95%CI) p-value OR (95%CI) p-value OR (95%CI) p-value Childbirth history G1 (no) Reference Reference Reference G2 (yes) 2.58 (2.19, 3.05) 0.0000 2.21 (1.87, 2.63) 0.0000 4.17 (3.09, 5.62) 0.0000 Birth number 1 Reference Reference Reference 2 1.14 (0.97, 1.34) 0.1074 1.12 (0.95, 1.32) 0.1935 1.08 (0.85, 1.36) 0.5429 3 1.41 (1.19, 1.67) 0.0001 1.34 (1.12, 1.60) 0.0012 1.33 (1.03, 1.72) 0.0019 4 ~ 8 1.81 (1.53, 2.16) 0.0000 1.74 (1.45, 2.10) 0.0000 1.72 (1.31, 2.27) 0.0001 >=8 3.32 (2.07, 5.40) 0.0002 3.37 (2.05, 5.60) 0.0000 3.56 (2.05, 6.23) 0.0000 Age at first birth =35 0.83 (0.52, 1.30) 0.4319 1.03 (0.64, 1.64) 0.8935 1.08 (0.64, 1.79) 0.7722 Age at last birth =35 1.08 (0.92, 1.26) 0.3278 1.22 (1.04, 1.44) 0.0160 1.03 (0.84, 1.26) 0.7668 Birth interval cycle =10 years 1.32 (1.13, 1.54) 0.0004 1.31 (1.11, 1.54) 0.0015 0.90 (0.72, 1.14) 0.3847 Model 1 without adjustments. Model 2 was additionally adjusted for race, education level, poverty and BMI. Model 3 was additionally adjusted for birth number, age at first birth, age at last birth and birth interval cycle. To examine potential differences in the relationship between childbirth experience and arthritis in specific populations, we conducted subgroup analyses and interaction tests by race, education level, poverty ratio, BMI, and RC levels. As showed in Fig. 4 , significant interactions were found in r education level and BMI. Interestingly, although it would also increase the risk of arthritis, the OR of obesity and overweight women were lower than that of normal weight women (P for interaction = 0.022). Effects of blood lipid indexes Firstly, RCS curves were adopted to display the association between the levels of blood lipid indexes and the risk of arthritis caused by childbirth experience. After adjusting for multiple variables, evidence for a nonlinear (L-shaped) relationship were observed in blood triglyceride and RC (p for nonlinearity < .001) (Fig. 5 A, B). However, there were no nonlinear (L-shaped) relationship between blood TC, LDL-C, HDL-C and the odds ratio (Supplement Fig. 1 ). Secondly, to clarify whether blood RC play an intermediary role between childbirth and arthritis, the parallel mediation analysis was carried out. Mediation analysis demonstrated that blood RC accounted for 8.45% of observed association between childbirth and arthritis (p < 0.001, Fig. 5 C). No significant mediating effects were found in other indexes. Third, WQS regression models was used to evaluate the impact of blood lipid indexes on the risk of arthritis caused by childbirth. Blood remnant cholesterol was the highest WQS weigh among four cholesterols, with the highest contributions 0.63 (Fig. 4 D), followed by HDL-C (0.36). Next, an inflection point (1.94 mmol/L) was determined by threshold effect analysis. It was particularly noteworthy that it would significantly increase the risk of arthritis caused by childbirth when the level lower than 1.94 mmol/L. The OR and 95% CIs was 2.02 (1.69, 2.42) (p < 0.0001). Improvement of Physical activity In order to explore whether physical activity can improve the risk arthritis caused by childbirth experience, we preliminarily evaluated two physical activity variables, including vigorous recreational activities and moderate recreational activities. By logistic regression analysis, both physical activity variables could significantly reduce the risk of arthritis. The OR were 0.80 and 0.36 for moderate recreational activities and vigorous recreational activities, respectively (p < 0.001, Supplement Fig. 2 ). At the same time, the levels of TC and LDL-C could be reduced by vigorous recreational activities, while HDL-C significantly increased, and then the level of RC was significantly decreased (p < 0.001, Table 4 ). Moderate recreational activities could significantly increase the level of HDL-C, and eventually led to the decrease of RC level (p < 0.001). As shown in Fig. 6 , RCS curves were confirmed that there was a nonlinear (U-shaped) relationship between vigorous recreational activities and the risk of arthritis (p for nonlinearity < 0.001) (Fig. 6 A). However, there was no nonlinear relationship in moderate recreational activities (Supplement Fig. 3 ). Threshold effect analysis found an inflection point for vigorous recreational activities (35 minutes on a typical day). It would significantly reduce the risk of arthritis caused by childbirth when the level lower than 35 minutes/day. The OR and 95% CIs was 0.92 (0.89, 0.96) (p < 0.0001). However, vigorous recreational activities for more than 35 minutes every day would increase the risk of arthritis (OR = 1.02, p = 0.0196). Additionally, smooth curve fitting also clarified the improvement of vigorous recreational activities (Fig. 6 B). Table 4 Comparison of cholesterol levels according to physical activity variables n TC (mmol/L) LDL-C (mmol/L) HDL-C (mmol/L) Remnant cholesterol (mmol/L) Vigorous recreational activities No 5385 5.028 ± 1.067 2.947 ± 0.924 1.495 ± 0.418 0.586 ± 0.316 Yes 1104 4.876 ± 1.013 2.789 ± 0.876 1.627 ± 0.432 0.46 ± 0.278 p-value < 0.001 < 0.001 < 0.001 < 0.001 Moderate recreational activities No 3884 4.999 ± 1.067 2.925 ± 0.924 1.484 ± 0.419 0.59 ± 0.32 Yes 2605 5.006 ± 1.049 2.913 ± 0.908 1.567 ± 0.425 0.527 ± 0.299 p-value 0.791 0.581 < 0.001 < 0.001 Discussion This study leveraged NHANES data to systematically evaluate the interplay between childbirth history, lipid metabolism, and arthritis risk in women. Our findings revealed that women with childbirth experience had a significantly higher risk of arthritis compared to nulliparous women. Notably, parity amplified arthritis risk in a dose-dependent manner, with higher live birth numbers and prolonged interpregnancy intervals exacerbating susceptibility. Residual cholesterol (RC) emerged as a critical mediator, accounting for 8.45% of the association between childbirth and arthritis, while vigorous physical activity demonstrated a U-shaped relationship with risk reduction. These results underscore the long-term metabolic and inflammatory consequences of reproductive events, offering novel insights into arthritis prevention strategies tailored to women with childbirth histories. The observed association between parity and arthritis aligns with prior studies suggesting cumulative joint stress from repeated pregnancies or persistent metabolic dysregulation as plausible mechanisms. For instance, Pang et al 17 reported that age at first birth and live birth numbers correlated with OA risk, though inconsistencies exist for RA 18 . Our analysis reconciles these discrepancies by demonstrating that mechanical strain from multiparity may predominantly drive OA, while metabolic alterations, particularly lipid abnormalities, contribute broadly to arthritis subtypes. Furthermore, the absence of an association between advanced maternal age and arthritis suggests that reproductive timing may indirectly influence arthritis risk through metabolic adaptations rather than direct hormonal effects. A pivotal finding is the role of RC, which in bridging childbirth and arthritis. RC levels were elevated in parous women and linearly associated with arthritis risk. This aligns with Yan et al 21 , who identified RC as a pro-inflammatory driver in RA. Intriguingly, HDL cholesterol exhibited no independent association with arthritis in adjusted models, contradicting studies linking low HDL to RA 22 . This discrepancy may reflect HDL dysfunction in chronic inflammatory states, where its anti-inflammatory capacity is compromised 38 . The nonlinear (L-shaped) relationship between triglycerides/RC and arthritis risk implies a threshold effect: modest lipid elevations may suffice to trigger joint damage, while extreme levels overwhelm compensatory mechanisms. Mediation analysis further highlights that RC explains only a fraction of the parity-arthritis link, suggesting additional pathways, such as oxidative stress, epigenetic reprogramming, or persistent immune activation, which warrant exploration. Vigorous physical activity reduced arthritis risk but exhibited a U-shaped relationship, with excessive exercise (> 35 minutes/day) paradoxically increasing odds. This mirrors meta-analyses showing moderate exercise improves joint health, while extreme regimens associated with transient immune dysfunction, elevated inflammatory biomarkers 39 . Mechanistically, moderate activity enhances HDL functionality 40 , but prolonged high-intensity exercise may induce oxidative stress or mechanical joint injury. Threshold analyses identified 35 minutes/day as optimal, aligning with American Heart Association guidelines 41 . Notably, vigorous activity also improved lipid profiles by lowering LDL-C and RC, underscoring its dual cardiometabolic and musculoskeletal benefits. However, several limitations merit consideration. At first, the study's cross-sectional design limits the ability to establish causality. Second, the measurement of physical activity relied on self-reported data, which is susceptible to recall bias. Despite adjusting for several potential confounders, there may be residual or unmeasured factors that could influence the relationship between childbirth history and arthritis, such as dietary patterns, genetic factors. Third, RC was calculated indirectly (TC − LDL-C − HDL-C), which may underestimate true RC levels compared to direct assays. Finally, NHANES lacks detailed joint imaging data, limiting subtype-specific analyses (OA vs. RA). In conclusion, childbirth history is a significant yet underrecognized risk factor for arthritis in women, mediated in part by persistent lipid abnormalities, particularly elevated RC. Reproductive intensity (birth numbers, interpregnancy intervals) further modulates risk, while physical activity offers protective benefits. These insights advocate for integrated approaches to women’s health that bridge reproductive, metabolic, and musculoskeletal care, ultimately reducing the global burden of arthritis. Disclosure of interests None declared. The authors declare that they have no competing interests. Declarations Disclosure of interests None declared. The authors declare that they have no competing interests. Author contributions Bin Yu, Huiyan Wang and Ming Zhang conceived the study and carried out the assays. Bin Yu and Huiyan Wang wrote and reviewed the manuscript. Ethics Approval and Consent to Participate This study was deemed exempt from ethical review and informed consent. Funding This study was funded by Project funding for the training of high-level health professionals in Changzhou (2022CZZY007, 2022CZLJ023). Acknowledgements We thank all of the project participants for their contributions. Availability of data and materials The questionnaire and datasets used are available from the corresponding author on request. References Callahan LF, Rao J, Boutaugh M. Arthritis and women's health: prevalence, impact, and prevention. Am J Prev Med. 1996;12:401–9. 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Int J Gynaecol Obstet. 2025;168:800–11. Jones PAT, et al. Impact of postpartum physical activity on cardiometabolic health, breastfeeding, injury and infant growth and development: a systematic review and meta-analysis. Br J Sports Med. 2025;59:539–49. Agbaje AO. Associations of Sedentary Time and Physical Activity From Childhood With Lipids: A 13-Year Mediation and Temporal Study. J Clin Endocrinol Metab. 2024;109:e1494–505. Barone Gibbs B et al. , . Physical Activity as a Critical Component of First-Line Treatment for Elevated Blood Pressure or Cholesterol: Who, What, and How? A Scientific Statement From the American Heart Association. Hypertension (Dallas, Tex.: 1979) 78, e26-e37 (2021). Fang J, Alderman MH. Serum uric acid and cardiovascular mortality the NHANES I epidemiologic follow-up study, 1971–1992. National Health and Nutrition Examination Survey. JAMA. 2000;283:2404–10. Alderman MH, Cohen H, Madhavan S. Dietary sodium intake and mortality: the National Health and Nutrition Examination Survey (NHANES I). Lancet (London England). 1998;351:781–5. Zeng CM, He J, Wang DC, Xie H. Association between triglyceride levels and rheumatoid arthritis prevalence in women: a cross-sectional study of NHANES (1999–2018). BMC Womens Health. 2025;25:129. Chen Z, et al. Association between remnant cholesterol (RC) and endometriosis: a cross-sectional study based on NHANES data. Lipids Health Dis. 2025;24:2. Qian S, et al. Remnant Cholesterol and Common Carotid Artery Intima-Media Thickness in Patients With Ischemic Stroke. Circ Cardiovasc Imaging. 2021;14:e010953. Dang K, et al. The association between triglyceride-glucose index and its combination with obesity indicators and cardiovascular disease: NHANES 2003–2018. Cardiovasc Diabetol. 2024;23:8. Guo HJ, Ye YL, Gao YF, Liu ZH. Age at first birth is associated with the likelihood of frailty in middle-aged and older women: A population-based analysis from NHANES 1999–2018. Maturitas. 2024;181:107904. Chen HL, et al. The association between the neutrophil-to-lymphocyte ratio and type 2 diabetes mellitus: a cross-sectional study. BMC Endocr disorders. 2024;24:107. Lui DTW, et al. The association of HDL-cholesterol levels with incident major adverse cardiovascular events and mortality in 0.6 million individuals with type 2 diabetes: a population-based retrospective cohort study. BMC Med. 2024;22:586. Nieman DC, Wentz LM. The compelling link between physical activity and the body's defense system. J sport health Sci. 2019;8:201–17. Stanton KM, et al. Moderate- and High-Intensity Exercise Improves Lipoprotein Profile and Cholesterol Efflux Capacity in Healthy Young Men. J Am Heart Association. 2022;11:e023386. Surgeon General's report on physical activity and health. Centers Disease Control Prev Jama. 1996;276:522. Additional Declarations No competing interests reported. Supplementary Files SFigure.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-6597672","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":454884586,"identity":"25637607-80b9-4c02-a2ca-ad1d82159687","order_by":0,"name":"Huiyan Wang","email":"","orcid":"","institution":"Changzhou Medical Center of Nanjing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Huiyan","middleName":"","lastName":"Wang","suffix":""},{"id":454884587,"identity":"ee6ecd2a-a735-413f-8b28-b60e69061721","order_by":1,"name":"Ming Zhang","email":"","orcid":"","institution":"Changzhou Medical Center of Nanjing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Ming","middleName":"","lastName":"Zhang","suffix":""},{"id":454884588,"identity":"306c66dd-96ea-429d-a7d0-22a611d29529","order_by":2,"name":"Bin Yu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAvklEQVRIiWNgGAWjYBACA2YQWcEAphh4iNdyhiQtIIKxDcojSos5O+8xad55d9h1ZyQwPnjbxiBvTkiLZTNfmjTvtmfMZjcSmA3ntjEY7mwg5LDDPGZALYdBWtikedsYEgwOEKVlDlgL+28StDRAbGEmSotlM4+x5ZxjQC1nHjZLzjknYbiBkBZz/jOGN97UHE42O5588MObMht5grYAAYsEkEgGxk4DkJYgrB4ImD8ACTuilI6CUTAKRsHIBACe8TlDTlQY9QAAAABJRU5ErkJggg==","orcid":"","institution":"Changzhou Medical Center of Nanjing Medical University","correspondingAuthor":true,"prefix":"","firstName":"Bin","middleName":"","lastName":"Yu","suffix":""}],"badges":[],"createdAt":"2025-05-06 00:08:07","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6597672/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6597672/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":82714097,"identity":"a7b64e81-8ac3-4b89-8e7f-19cba33f7a05","added_by":"auto","created_at":"2025-05-14 11:58:11","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":94379,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFlowchart of participants selection from the NHANES in present study.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-6597672/v1/5bb3d7b9b7d2e9440e9728c4.png"},{"id":82713174,"identity":"b2701b83-847a-4a7a-96f0-208941a78092","added_by":"auto","created_at":"2025-05-14 11:50:11","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":43647,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTrend of fertility in the United States.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-6597672/v1/757e4dee9a409815c9cf8d2b.png"},{"id":82713177,"identity":"d065042e-335e-40e8-95e4-b00bd85743d6","added_by":"auto","created_at":"2025-05-14 11:50:11","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":78934,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRelationship between reproduction-related indicators and OR\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-6597672/v1/8d63096aa5b09edda514821e.png"},{"id":82713179,"identity":"ae8d2417-67ca-4520-bc04-2152734a4f5d","added_by":"auto","created_at":"2025-05-14 11:50:11","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":134821,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSubgroup analysis of associations between childbirth and arthritis.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-6597672/v1/302fb3584337879218e68084.png"},{"id":82714547,"identity":"f32cb1f9-6329-486e-8d31-1a12598b4178","added_by":"auto","created_at":"2025-05-14 12:06:11","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":169987,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eBlood lipid indexes in the association between childbirth and arthritis.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA. Restricted cubic splines curves of remnant cholesterol\u003c/p\u003e\n\u003cp\u003eB. Restricted cubic splines curves of triglyceride\u003c/p\u003e\n\u003cp\u003eC. Mediation of remnant cholesterol in the association between childbirth and the risk of arthritis\u003c/p\u003e\n\u003cp\u003eD. WQS regression model of blood lipid indexes\u003c/p\u003e\n\u003cp\u003eResults were adjusted for race, education level, poverty income ratio and BMI.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-6597672/v1/4f77a3b1907fe54318fbb847.png"},{"id":82714101,"identity":"d65cbec1-6620-4a81-9d5c-0ec5fe50039e","added_by":"auto","created_at":"2025-05-14 11:58:11","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":107875,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eVigorous recreational activities reduce the risk of arthritis.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA. Restricted cubic splines curves\u003c/p\u003e\n\u003cp\u003eB. Smooth curve fitting of blood lead\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-6597672/v1/f3955999a9e2b572f38bf410.png"},{"id":83480916,"identity":"cc4f7e32-42d3-45c5-b380-e651d81fe898","added_by":"auto","created_at":"2025-05-27 06:47:07","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1884103,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6597672/v1/33270c85-17b2-4690-92cd-1ba2d5db76d9.pdf"},{"id":82713183,"identity":"4790298e-d0e9-476a-a19d-72d92851f2c7","added_by":"auto","created_at":"2025-05-14 11:50:11","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":271085,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"SFigure.docx","url":"https://assets-eu.researchsquare.com/files/rs-6597672/v1/89a37f75be12490822488540.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Childbirth History Increases Arthritis Risk in Women: The Role of Lipid Metabolism and Physical Activity","fulltext":[{"header":"Highlights","content":"\u003col\u003e\n \u003cli\u003eThe first large-scale epidemiological investigation systematically evaluated the relationship between childbirth and arthritis risk in women, with a focus on elucidating the mediating role of blood lipid indexes (particularly remnant cholesterol) and the protective effects of physical activity.\u003c/li\u003e\n \u003cli\u003eChildbirth is independently associated with a 2.21~4.17-fold increased risk of arthritis in women.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eElevated blood remnant cholesterol levels mediate approximately 8.45% of this association, exhibiting a nonlinear threshold effect.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eThere was a nonlinear (U-shaped) relationship between vigorous recreational activities and the risk of arthritis (p for nonlinearity \u0026lt;0.001), and an inflection point (35 minutes on a typical day) was found.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Introduction","content":"\u003cp\u003eArthritis is one of the most prevalent chronic conditions in the world and the most prevalent chronic condition in women\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Osteoarthritis (OA) and rheumatoid arthritis (RA) are the most common forms, contributing to chronic pain, reduced mobility, and diminished quality of life. In addition, arthritis is one of the leading causes of disability and limitations in activities of daily living, and its economic, psychological, and social impact is enormous. Women exhibit unique risk profiles influenced by hormonal fluctuations\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e, genetic predisposition\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e, and lifestyle factors\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Despite advances in treatment, arthritis remains a major public health challenge, necessitating deeper insights into modifiable risk factors, particularly those linked to women\u0026rsquo;s life-course events.\u003c/p\u003e \u003cp\u003ePregnancy and childbirth are cardinal events in a woman's life course, exerting profound and enduring impacts on both short-term and long-term health\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e, including physiology, metabolism and psychology\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. From a physiological perspective, pregnancy induces a cascade of adaptations across multiple organ systems, especially cardiovascular system\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e and endocrine system\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e, and so on. Beyond their immediate role in reproduction, these experiences are increasingly recognized for their dual impact on long-term health trajectories. Previous studies have predominantly focused on the adverse effects of pregnancy complications on women's health\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Recently, epidemiological evidence highlights potential protective effects of parity\u003csup\u003e\u003cspan additionalcitationids=\"CR13 CR14\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. However, the relationship between reproductive history and arthritis remains unclear. Previous studies mainly focused on the pregnant risks and management of women with arthritis or rheumatoid diseases\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. Existing literature on reproductive factors and arthritis risk is inconclusive. Pang \u003cem\u003eet al\u003c/em\u003e\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e reported that there was no reliable causal relationship between age at menarche/age at menopause and OA, but an increase in age at first live birth and umber of live births was associated with an increased risk of OA. However, Ranjbaran\u0026rsquo;s group\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e didn\u0026rsquo;t find a significant correlation between RA and reproductive related indicators (including number of pregnancies, age at first pregnancy, duration of breastfeeding and number of children).\u003c/p\u003e \u003cp\u003eIt is well known that dyslipidemia is increasingly recognized as a contributor to arthritis pathogenesis\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. Recent attention has turned to remnant cholesterol (RC) as a potent pro-inflammatory agent, and it can increase the risk of RA\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. High-density lipoprotein cholesterol (HDL-C) exhibits paradoxical roles in arthritis. Choudhury reported that low HDL cholesterol levels were more common in RA patients\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e, but Giacaglia obtained the opposite result\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. In addition, pregnancy imposes profound, lasting changes on lipid metabolism. During gestation, maternal cholesterol levels rise to support fetal neurodevelopment, and characterized by increases in both low-density lipoprotein cholesterol (LDL-C) and triglyceride levels\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. Postpartum, these elevations often persist, particularly in women with gestational dyslipidemia or excessive weight retention\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e,\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. Despite these insights, no study has systematically evaluated how reproductive timing, parity, and lipid alterations collectively influence arthritis. Furthermore, physical activity was considered cloud improve postpartum woman health without adversely impacting breast milk supply or quality, infant growth or maternal injury\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. And it was also an effective method to reduce blood lipid\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e,\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eHere, in order to explore the association between childbirth experience and risk of arthritis, we investigated seven cycles of the National Health and Nutrition Examination Survey (NHANES)\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e,\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. We clarified their relationship firstly, and discussed the role of blood lipids (especially cholesterol). Then, we explored the improvement effect of physical activity. This study offers new insights into potential health risks associated with childbirth experience, and hope to contribute to improving public health outcomes.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData source and study population\u003c/h2\u003e \u003cp\u003eThe cross-sectional study was from seven cycles of NHANES (2007\u0026thinsp;~\u0026thinsp;2020). The participant\u0026rsquo;s selection is illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Of 66148 initial subjects, 32793 were excluded due to male sex. 16627 were excluded due to incomplete data of age, education level, race, poverty ratio and body mass index (BMI). 9184 were excluded due to missing the data of blood lipid indexes.1053 were excluded due to missing the information of pregnancy, childbirth and arthritis. Finally, 6491 women were included in this study. According to their experience of pregnancy and childbirth, the subjects were divided into two groups: never pregnancy women (G1, n\u0026thinsp;=\u0026thinsp;2144), and had childbirth (G2, n\u0026thinsp;=\u0026thinsp;4347).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eDefinition of pregnancy and childbirth history\u003c/h3\u003e\n\u003cp\u003ePregnancy history was measured by the following question: \u0026ldquo;Ever been pregnant? (RHQ131)\u0026rdquo;, including current pregnancy, live births, miscarriages, stillbirths, tubal pregnancies and abortions. Women who answer yes were considered as having pregnancy. While the participants who answer no were considered as never pregnancy (G1). Similarly, childbirth history and birth number were defined according to the question: \u0026ldquo;How many deliveries live birth result? (RHQ171)\u0026rdquo;. Women who answer the number of live births more than one were considered as having childbirth (G2). Next, the definition of age at first birth (AFB) and age at last birth (ALB) were based on the Questionnaire Data of \u0026ldquo;Age at first live birth (RHQ180)\u0026rdquo; and \u0026ldquo;Age at last live birth (RHD190)\u0026rdquo; respectively. Birth interval cycle was calculated as ALB-AFB.\u003c/p\u003e\n\u003ch3\u003eDefinition of arthritis\u003c/h3\u003e\n\u003cp\u003eJust as the previous study\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e, arthritis was measured by the following question (MCQ160a): Has a doctor or other health professional ever told you that you had arthritis? Women who answer yes were considered as have arthritis.\u003c/p\u003e\n\u003ch3\u003eMeasurements of blood lipid indexes\u003c/h3\u003e\n\u003cp\u003eWomen's blood lipid index in questionnaire were obtained from laboratory data, including triglyceride (mmol/L), total cholesterol (TC, mmol/L), LDL-cholesterol (LDL-C, mmol/L) and HDL-cholesterol (HDL-C, mmol/L). According to the study\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e, remnant cholesterol (RC) was calculated as deducting the levels of LDL-C and HDL-C from TC. According to the literature\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e, we convert the unit of sitting time in hours and divide it into four levels: Q1(\u0026lt;\u0026thinsp;0.43 mmol/L), Q2 (0.41\u0026thinsp;~\u0026thinsp;0.61 mmol/L), Q3 (0.61\u0026thinsp;~\u0026thinsp;0.88 mmol/L) and Q4 (\u0026thinsp;\u0026gt;\u0026thinsp;=\u0026thinsp;0.88 mmol/L). Meanwhile, Q1 was defined as the reference in the follow-up study.\u003c/p\u003e\n\u003ch3\u003eMeasurements of physical Activity\u003c/h3\u003e\n\u003cp\u003ePhysical Activity were obtained from questionnaire data, including vigorous recreational activities (PAQ650) and moderate recreational activities (PAQ665). The time of their activities were extracted from PAD660 and PAD675 respectively, and the unit was minutes.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eOther covariates\u003c/h2\u003e \u003cp\u003eSimilar to some other studies\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e,\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e, age, gender, race education level, race and poverty ratio were obtained from demographics data. BMI and weight were collected from examination data.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eDecisionLinnc1.0 software\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e was employed for data analysis, which is a platform that integrates multiple programming language environments. Logistic regression analysis model was employed to across three distinct models to examine the relationship between childbirth experience and arthritis. Subgroup analyses were also conducted. Next, restricted cubic splines (RCS) was utilized to explore potential non-linear relationships between blood lipid indexes and the risk of arthritis caused by childbirth experience. Weighted Quantile Sum (WQS) regression was used to explore the overall effect of blood lipid indexes. P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eBaseline participant characteristics\u003c/h2\u003e \u003cp\u003eA total of 6491 participants with complete data from NHANES (2007\u0026thinsp;~\u0026thinsp;2020) were included in this study. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e2\u003c/span\u003e, the median (Q1\u0026thinsp;~\u0026thinsp;Q3) of birth number was 3 (2\u0026thinsp;~\u0026thinsp;4) in the United States, and the number of births in 2020 significantly decreased compared with 2007 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). At the same time, in recent years, the age of last birth has become more younger (p\u0026thinsp;=\u0026thinsp;0.006). However, there were no significant difference in age at fist birth (p\u0026thinsp;=\u0026thinsp;0.821). Therefore, the birth interval cycle also showed a significant downward trend (p\u0026thinsp;=\u0026thinsp;0.020). Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents the baseline characteristics of the participants according to childbirth history. Of 6491 participants, 2144 (33.03%) women occurred arthritis. Compared to never pregnancy women(G1), the prevalence of arthritis was significantly increased in the participants with childbirth experience (G2) (36.03% vs 17.94%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). At the same time, the women who had experience of childbirth showed abnormalities in several blood lipid indexes, which are characterized by a significant decrease in HDL-C and a significant increase in other indexes (triglyceride, TC, LDL-C and RC). In addition, they were also generally older (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and had higher BMI (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline participant characteristics according to birth history\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariable Names\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eChildbirth history\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eG1 (no)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eG2 (yes)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003en\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6491\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1076\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5415\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge (year)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50.109\u0026thinsp;\u0026plusmn;\u0026thinsp;17.552\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37.447\u0026thinsp;\u0026plusmn;\u0026thinsp;17.376\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e52.625\u0026thinsp;\u0026plusmn;\u0026thinsp;16.467\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRace (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMexican American\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e924 (14.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e116 (10.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e808 (14.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther Hispanic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e695 (10.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e98 (9.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e597 (11.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-Hispanic White\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2781 (42.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e475 (44.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2306 (42.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-Hispanic Black\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1352 (20.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e201 (18.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1151 (21.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther Race\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e739 (11.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e186 (17.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e553 (10.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePoverty income ratio\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.429\u0026thinsp;\u0026plusmn;\u0026thinsp;1.613\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.729\u0026thinsp;\u0026plusmn;\u0026thinsp;1.677\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.369\u0026thinsp;\u0026plusmn;\u0026thinsp;1.594\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;5.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5452 (83.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e846 (78.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4606 (85.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;=5.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1039 (16.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e230 (21.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e809 (14.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducation level (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLess than 9th grade\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e555 (8.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34 (3.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e521 (9.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9-11th grade\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e857 (13.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50 (4.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e807 (14.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh school graduate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1410 (21.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e167 (15.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1243 (22.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSome college\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2093 (32.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e379 (35.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1714 (31.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCollege graduate or above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1576 (24.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e446 (41.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1130 (20.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBMI (kg/m2)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29.809\u0026thinsp;\u0026plusmn;\u0026thinsp;7.852\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28.587\u0026thinsp;\u0026plusmn;\u0026thinsp;9.032\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30.052\u0026thinsp;\u0026plusmn;\u0026thinsp;7.573\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNormal weight (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1917 (29.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e473 (43.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1444 (26.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverweight (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1836 (28.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e238 (22.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1598 (29.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObesity (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2738 (42.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e365 (33.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2373 (43.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTriglyceride\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e109.138\u0026thinsp;\u0026plusmn;\u0026thinsp;60.569\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e93.243\u0026thinsp;\u0026plusmn;\u0026thinsp;53.481\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e112.297\u0026thinsp;\u0026plusmn;\u0026thinsp;61.398\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal-cholesterol\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.002\u0026thinsp;\u0026plusmn;\u0026thinsp;1.059\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.828\u0026thinsp;\u0026plusmn;\u0026thinsp;1.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.036\u0026thinsp;\u0026plusmn;\u0026thinsp;1.066\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLDL-cholesterol\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.92\u0026thinsp;\u0026plusmn;\u0026thinsp;0.918\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.794\u0026thinsp;\u0026plusmn;\u0026thinsp;0.865\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.945\u0026thinsp;\u0026plusmn;\u0026thinsp;0.926\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHDL-cholesterol\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.517\u0026thinsp;\u0026plusmn;\u0026thinsp;0.423\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.553\u0026thinsp;\u0026plusmn;\u0026thinsp;0.421\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.51\u0026thinsp;\u0026plusmn;\u0026thinsp;0.424\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRemnant cholesterol\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.564\u0026thinsp;\u0026plusmn;\u0026thinsp;0.314\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.482\u0026thinsp;\u0026plusmn;\u0026thinsp;0.277\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.581\u0026thinsp;\u0026plusmn;\u0026thinsp;0.318\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2614 (40.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e557 (51.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2057 (37.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1632 (25.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e256 (23.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1376 (25.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1336 (20.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e172 (15.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1164 (21.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e909 (14.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e91 (8.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e818 (15.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eArthritis\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWithout\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4347 (66.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e883 (82.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3464 (63.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHad\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2144 (33.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e193 (17.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1951 (36.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e compared the levels of blood lipid according to arthritis or reproductive-related indicators respectively. Notably, the levels of TC and RC were significantly increased in the women had arthritis (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). However, there were no significant differences in the levels of LDL-C and HDL-C (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Meanwhile, the more birth number and the longer birth interval cycle, the higher the level of RC.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of cholesterol levels\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTC\u003c/p\u003e \u003cp\u003e(mmol/L)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLDL-C\u003c/p\u003e \u003cp\u003e(mmol/L)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHDL-C\u003c/p\u003e \u003cp\u003e(mmol/L)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRemnant cholesterol\u003c/p\u003e \u003cp\u003e(mmol/L)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eArthritis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWithout\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4347\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.951\u0026thinsp;\u0026plusmn;\u0026thinsp;1.043\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.906\u0026thinsp;\u0026plusmn;\u0026thinsp;0.901\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.512\u0026thinsp;\u0026plusmn;\u0026thinsp;0.405\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.534\u0026thinsp;\u0026plusmn;\u0026thinsp;0.303\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHad\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.104\u0026thinsp;\u0026plusmn;\u0026thinsp;1.085\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.949\u0026thinsp;\u0026plusmn;\u0026thinsp;0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.528\u0026thinsp;\u0026plusmn;\u0026thinsp;0.458\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.627\u0026thinsp;\u0026plusmn;\u0026thinsp;0.324\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.073\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.147\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBirth number\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1106\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.95\u0026thinsp;\u0026plusmn;\u0026thinsp;1.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.887\u0026thinsp;\u0026plusmn;\u0026thinsp;0.919\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.518\u0026thinsp;\u0026plusmn;\u0026thinsp;0.417\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.545\u0026thinsp;\u0026plusmn;\u0026thinsp;0.321\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1790\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.084\u0026thinsp;\u0026plusmn;\u0026thinsp;1.064\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.982\u0026thinsp;\u0026plusmn;\u0026thinsp;0.935\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.53\u0026thinsp;\u0026plusmn;\u0026thinsp;0.445\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.572\u0026thinsp;\u0026plusmn;\u0026thinsp;0.311\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1271\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.039\u0026thinsp;\u0026plusmn;\u0026thinsp;1.067\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.951\u0026thinsp;\u0026plusmn;\u0026thinsp;0.917\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.403\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.589\u0026thinsp;\u0026plusmn;\u0026thinsp;0.318\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u0026thinsp;~\u0026thinsp;8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1173\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.044\u0026thinsp;\u0026plusmn;\u0026thinsp;1.056\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.942\u0026thinsp;\u0026plusmn;\u0026thinsp;0.919\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.487\u0026thinsp;\u0026plusmn;\u0026thinsp;0.422\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.615\u0026thinsp;\u0026plusmn;\u0026thinsp;0.319\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;=8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u0026thinsp;\u0026plusmn;\u0026thinsp;1.159\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.881\u0026thinsp;\u0026plusmn;\u0026thinsp;1.029\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.452\u0026thinsp;\u0026plusmn;\u0026thinsp;0.321\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.668\u0026thinsp;\u0026plusmn;\u0026thinsp;0.348\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.028\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.038\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge at first birth\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4152\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.038\u0026thinsp;\u0026plusmn;\u0026thinsp;1.057\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.956\u0026thinsp;\u0026plusmn;\u0026thinsp;0.914\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.499\u0026thinsp;\u0026plusmn;\u0026thinsp;0.419\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.583\u0026thinsp;\u0026plusmn;\u0026thinsp;0.319\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;=35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.355\u0026thinsp;\u0026plusmn;\u0026thinsp;1.233\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.206\u0026thinsp;\u0026plusmn;\u0026thinsp;1.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.639\u0026thinsp;\u0026plusmn;\u0026thinsp;0.502\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.511\u0026thinsp;\u0026plusmn;\u0026thinsp;0.302\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.088\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge at last birth\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3930\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.025\u0026thinsp;\u0026plusmn;\u0026thinsp;1.056\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.947\u0026thinsp;\u0026plusmn;\u0026thinsp;0.914\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.498\u0026thinsp;\u0026plusmn;\u0026thinsp;0.415\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.58\u0026thinsp;\u0026plusmn;\u0026thinsp;0.321\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;=35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e959\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.133\u0026thinsp;\u0026plusmn;\u0026thinsp;1.042\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.004\u0026thinsp;\u0026plusmn;\u0026thinsp;0.904\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.541\u0026thinsp;\u0026plusmn;\u0026thinsp;0.443\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.588\u0026thinsp;\u0026plusmn;\u0026thinsp;0.32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.711\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBirth interval cycle\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;5 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1710\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.036\u0026thinsp;\u0026plusmn;\u0026thinsp;1.102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.959\u0026thinsp;\u0026plusmn;\u0026thinsp;0.945\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.522\u0026thinsp;\u0026plusmn;\u0026thinsp;0.439\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.554\u0026thinsp;\u0026plusmn;\u0026thinsp;0.314\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u0026thinsp;~\u0026thinsp;10 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1319\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.044\u0026thinsp;\u0026plusmn;\u0026thinsp;1.032\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.962\u0026thinsp;\u0026plusmn;\u0026thinsp;0.901\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.498\u0026thinsp;\u0026plusmn;\u0026thinsp;0.409\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.584\u0026thinsp;\u0026plusmn;\u0026thinsp;0.317\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;=10 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1206\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.061\u0026thinsp;\u0026plusmn;\u0026thinsp;1.036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.963\u0026thinsp;\u0026plusmn;\u0026thinsp;0.899\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.479\u0026thinsp;\u0026plusmn;\u0026thinsp;0.407\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.618\u0026thinsp;\u0026plusmn;\u0026thinsp;0.325\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.597\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.121\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eAssociations between childbirth experience and arthritis\u003c/h2\u003e \u003cp\u003eWe have established three models before and after adjusting for confounding factors respectively. As shown in Table \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, three models established a statistically significant association between childbirth experience and arthritis. In the unadjusted model (Model 1), the risk of arthritis for the women had childbirth was significantly increased. The odds ratio (OR) and 95% confidence intervals (CIs) was 2.58 (2.19, 3.05) (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). After additionally adjusting for general data confounding factors such as race, education, poverty income ratio, BMI (Model 2), childbirth experience was still associated with an increased risk of arthritis (OR\u0026thinsp;=\u0026thinsp;2.21, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). Furthermore, model 3 still showed this trend of increasing risk after additionally adjusting for birth number, age at first birth, age at last birth and birth interval cycle (OR\u0026thinsp;=\u0026thinsp;4.17, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). In addition, the birth number and birth interval cycle would increase the risk of arthritis caused by childbirth experience (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e3\u003c/span\u003e). For example, compared with women who delivered one live birth, women who have more than three children had a significantly higher risk of arthritis. Meanwhile, if the birth interval exceeds 10 years, it would also significantly increase the risk. However, the woman of advanced maternal age didn\u0026rsquo;t increase the risk of arthritis, regardless of the age at first birth or age at last birth.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultivariable-adjust ORs and 95%CI of birth history and accelerated aging\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eModel 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eModel 2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eModel 3\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOR (95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eOR (95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eOR (95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChildbirth history\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG1 (no)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG2 (yes)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.58 (2.19, 3.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.21 (1.87, 2.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4.17 (3.09, 5.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.0000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBirth number\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.14 (0.97, 1.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.1074\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.12 (0.95, 1.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.1935\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.08 (0.85, 1.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.5429\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.41 (1.19, 1.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.34 (1.12, 1.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.33 (1.03, 1.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.0019\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u0026thinsp;~\u0026thinsp;8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.81 (1.53, 2.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.74 (1.45, 2.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.72 (1.31, 2.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;=8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.32 (2.07, 5.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.37 (2.05, 5.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.56 (2.05, 6.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.0000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge at first birth\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;=35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.83 (0.52, 1.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.4319\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.03 (0.64, 1.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.8935\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.08 (0.64, 1.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.7722\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge at last birth\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;=35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.08 (0.92, 1.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.3278\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.22 (1.04, 1.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0160\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.03 (0.84, 1.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.7668\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBirth interval cycle\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;5 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u0026thinsp;~\u0026thinsp;10 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.05 (0.90, 1.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.5245\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.00 (0.86, 1.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.9577\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.82 (0.68, 0.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.0368\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;=10 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.32 (1.13, 1.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.31 (1.11, 1.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.90 (0.72, 1.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.3847\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003eModel 1 without adjustments.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003eModel 2 was additionally adjusted for race, education level, poverty and BMI.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003eModel 3 was additionally adjusted for birth number, age at first birth, age at last birth and birth interval cycle.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTo examine potential differences in the relationship between childbirth experience and arthritis in specific populations, we conducted subgroup analyses and interaction tests by race, education level, poverty ratio, BMI, and RC levels. As showed in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e4\u003c/span\u003e, significant interactions were found in r education level and BMI. Interestingly, although it would also increase the risk of arthritis, the OR of obesity and overweight women were lower than that of normal weight women (P for interaction\u0026thinsp;=\u0026thinsp;0.022).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eEffects of blood lipid indexes\u003c/h2\u003e \u003cp\u003eFirstly, RCS curves were adopted to display the association between the levels of blood lipid indexes and the risk of arthritis caused by childbirth experience. After adjusting for multiple variables, evidence for a nonlinear (L-shaped) relationship were observed in blood triglyceride and RC (p for nonlinearity\u0026thinsp;\u0026lt;\u0026thinsp;.001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e5\u003c/span\u003eA, B). However, there were no nonlinear (L-shaped) relationship between blood TC, LDL-C, HDL-C and the odds ratio (Supplement Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Secondly, to clarify whether blood RC play an intermediary role between childbirth and arthritis, the parallel mediation analysis was carried out. Mediation analysis demonstrated that blood RC accounted for 8.45% of observed association between childbirth and arthritis (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e5\u003c/span\u003eC). No significant mediating effects were found in other indexes. Third, WQS regression models was used to evaluate the impact of blood lipid indexes on the risk of arthritis caused by childbirth. Blood remnant cholesterol was the highest WQS weigh among four cholesterols, with the highest contributions 0.63 (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e4\u003c/span\u003eD), followed by HDL-C (0.36). Next, an inflection point (1.94 mmol/L) was determined by threshold effect analysis. It was particularly noteworthy that it would significantly increase the risk of arthritis caused by childbirth when the level lower than 1.94 mmol/L. The OR and 95% CIs was 2.02 (1.69, 2.42) (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eImprovement of Physical activity\u003c/h2\u003e \u003cp\u003eIn order to explore whether physical activity can improve the risk arthritis caused by childbirth experience, we preliminarily evaluated two physical activity variables, including vigorous recreational activities and moderate recreational activities.\u003c/p\u003e \u003cp\u003eBy logistic regression analysis, both physical activity variables could significantly reduce the risk of arthritis. The OR were 0.80 and 0.36 for moderate recreational activities and vigorous recreational activities, respectively (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Supplement Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e2\u003c/span\u003e). At the same time, the levels of TC and LDL-C could be reduced by vigorous recreational activities, while HDL-C significantly increased, and then the level of RC was significantly decreased (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Moderate recreational activities could significantly increase the level of HDL-C, and eventually led to the decrease of RC level (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e6\u003c/span\u003e, RCS curves were confirmed that there was a nonlinear (U-shaped) relationship between vigorous recreational activities and the risk of arthritis (p for nonlinearity\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e6\u003c/span\u003eA). However, there was no nonlinear relationship in moderate recreational activities (Supplement Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Threshold effect analysis found an inflection point for vigorous recreational activities (35 minutes on a typical day). It would significantly reduce the risk of arthritis caused by childbirth when the level lower than 35 minutes/day. The OR and 95% CIs was 0.92 (0.89, 0.96) (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). However, vigorous recreational activities for more than 35 minutes every day would increase the risk of arthritis (OR\u0026thinsp;=\u0026thinsp;1.02, p\u0026thinsp;=\u0026thinsp;0.0196). Additionally, smooth curve fitting also clarified the improvement of vigorous recreational activities (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e6\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cb\u003eComparison of cholesterol levels according to physical activity variables\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTC\u003c/p\u003e \u003cp\u003e(mmol/L)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLDL-C\u003c/p\u003e \u003cp\u003e(mmol/L)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHDL-C\u003c/p\u003e \u003cp\u003e(mmol/L)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRemnant cholesterol\u003c/p\u003e \u003cp\u003e(mmol/L)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eVigorous recreational activities\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5385\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.028\u0026thinsp;\u0026plusmn;\u0026thinsp;1.067\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.947\u0026thinsp;\u0026plusmn;\u0026thinsp;0.924\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.495\u0026thinsp;\u0026plusmn;\u0026thinsp;0.418\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.586\u0026thinsp;\u0026plusmn;\u0026thinsp;0.316\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1104\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.876\u0026thinsp;\u0026plusmn;\u0026thinsp;1.013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.789\u0026thinsp;\u0026plusmn;\u0026thinsp;0.876\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.627\u0026thinsp;\u0026plusmn;\u0026thinsp;0.432\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.46\u0026thinsp;\u0026plusmn;\u0026thinsp;0.278\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eModerate recreational activities\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3884\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.999\u0026thinsp;\u0026plusmn;\u0026thinsp;1.067\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.925\u0026thinsp;\u0026plusmn;\u0026thinsp;0.924\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.484\u0026thinsp;\u0026plusmn;\u0026thinsp;0.419\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.59\u0026thinsp;\u0026plusmn;\u0026thinsp;0.32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2605\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.006\u0026thinsp;\u0026plusmn;\u0026thinsp;1.049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.913\u0026thinsp;\u0026plusmn;\u0026thinsp;0.908\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.567\u0026thinsp;\u0026plusmn;\u0026thinsp;0.425\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.527\u0026thinsp;\u0026plusmn;\u0026thinsp;0.299\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.791\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.581\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study leveraged NHANES data to systematically evaluate the interplay between childbirth history, lipid metabolism, and arthritis risk in women. Our findings revealed that women with childbirth experience had a significantly higher risk of arthritis compared to nulliparous women. Notably, parity amplified arthritis risk in a dose-dependent manner, with higher live birth numbers and prolonged interpregnancy intervals exacerbating susceptibility. Residual cholesterol (RC) emerged as a critical mediator, accounting for 8.45% of the association between childbirth and arthritis, while vigorous physical activity demonstrated a U-shaped relationship with risk reduction. These results underscore the long-term metabolic and inflammatory consequences of reproductive events, offering novel insights into arthritis prevention strategies tailored to women with childbirth histories.\u003c/p\u003e \u003cp\u003eThe observed association between parity and arthritis aligns with prior studies suggesting cumulative joint stress from repeated pregnancies or persistent metabolic dysregulation as plausible mechanisms. For instance, Pang \u003cem\u003eet al\u003c/em\u003e\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e reported that age at first birth and live birth numbers correlated with OA risk, though inconsistencies exist for RA\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. Our analysis reconciles these discrepancies by demonstrating that mechanical strain from multiparity may predominantly drive OA, while metabolic alterations, particularly lipid abnormalities, contribute broadly to arthritis subtypes. Furthermore, the absence of an association between advanced maternal age and arthritis suggests that reproductive timing may indirectly influence arthritis risk through metabolic adaptations rather than direct hormonal effects.\u003c/p\u003e \u003cp\u003eA pivotal finding is the role of RC, which in bridging childbirth and arthritis. RC levels were elevated in parous women and linearly associated with arthritis risk. This aligns with Yan \u003cem\u003eet al\u003c/em\u003e\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e, who identified RC as a pro-inflammatory driver in RA. Intriguingly, HDL cholesterol exhibited no independent association with arthritis in adjusted models, contradicting studies linking low HDL to RA\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. This discrepancy may reflect HDL dysfunction in chronic inflammatory states, where its anti-inflammatory capacity is compromised\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e. The nonlinear (L-shaped) relationship between triglycerides/RC and arthritis risk implies a threshold effect: modest lipid elevations may suffice to trigger joint damage, while extreme levels overwhelm compensatory mechanisms. Mediation analysis further highlights that RC explains only a fraction of the parity-arthritis link, suggesting additional pathways, such as oxidative stress, epigenetic reprogramming, or persistent immune activation, which warrant exploration.\u003c/p\u003e \u003cp\u003eVigorous physical activity reduced arthritis risk but exhibited a U-shaped relationship, with excessive exercise (\u0026gt;\u0026thinsp;35 minutes/day) paradoxically increasing odds. This mirrors meta-analyses showing moderate exercise improves joint health, while extreme regimens associated with transient immune dysfunction, elevated inflammatory biomarkers\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e. Mechanistically, moderate activity enhances HDL functionality\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e, but prolonged high-intensity exercise may induce oxidative stress or mechanical joint injury. Threshold analyses identified 35 minutes/day as optimal, aligning with American Heart Association guidelines\u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e. Notably, vigorous activity also improved lipid profiles by lowering LDL-C and RC, underscoring its dual cardiometabolic and musculoskeletal benefits.\u003c/p\u003e \u003cp\u003eHowever, several limitations merit consideration. At first, the study's cross-sectional design limits the ability to establish causality. Second, the measurement of physical activity relied on self-reported data, which is susceptible to recall bias. Despite adjusting for several potential confounders, there may be residual or unmeasured factors that could influence the relationship between childbirth history and arthritis, such as dietary patterns, genetic factors. Third, RC was calculated indirectly (TC\u0026thinsp;\u0026minus;\u0026thinsp;LDL-C\u0026thinsp;\u0026minus;\u0026thinsp;HDL-C), which may underestimate true RC levels compared to direct assays. Finally, NHANES lacks detailed joint imaging data, limiting subtype-specific analyses (OA vs. RA).\u003c/p\u003e \u003cp\u003eIn conclusion, childbirth history is a significant yet underrecognized risk factor for arthritis in women, mediated in part by persistent lipid abnormalities, particularly elevated RC. Reproductive intensity (birth numbers, interpregnancy intervals) further modulates risk, while physical activity offers protective benefits. These insights advocate for integrated approaches to women\u0026rsquo;s health that bridge reproductive, metabolic, and musculoskeletal care, ultimately reducing the global burden of arthritis.\u003c/p\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eDisclosure of interests\u003c/h2\u003e \u003cp\u003eNone declared. The authors declare that they have no competing interests.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eDisclosure of interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone declared. The authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBin Yu, Huiyan Wang\u003c/strong\u003e and \u003cstrong\u003eMing Zhang\u0026nbsp;\u003c/strong\u003econceived the study and carried out the assays.\u0026nbsp;\u003cstrong\u003eBin Yu\u003c/strong\u003e and \u003cstrong\u003eHuiyan Wang\u0026nbsp;\u003c/strong\u003ewrote and reviewed the manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics Approval and Consent to Participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was deemed exempt from ethical review and informed consent.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was funded by Project funding for the training of high-level health professionals in Changzhou (2022CZZY007, 2022CZLJ023).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank all of the project participants for their contributions.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe questionnaire and datasets used are available from the corresponding author on request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eCallahan LF, Rao J, Boutaugh M. Arthritis and women's health: prevalence, impact, and prevention. Am J Prev Med. 1996;12:401\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePrevalence of doctor-diagnosed. arthritis and arthritis-attributable activity limitation\u0026ndash;United States, 2003\u0026ndash;2005. MMWR Morb Mortal Wkly Rep. 2006;55:1089\u0026ndash;92.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhao H, Yu F, Wu W. The Mechanism by Which Estrogen Level Affects Knee Osteoarthritis Pain in Perimenopause and Non-Pharmacological Measures. Int J Mol Sci 26(2025).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNamavari N, Jokar M, Ghodsian A, Jahromi HK, Rahmanian V. Menopausal state and rheumatoid arthritis: a systematic review and meta-analysis. BMC Rheumatol. 2024;8:48.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXu Y, Wu Q. 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Med (Baltim). 2025;104:e41362.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRanjbaran ME, Kazemi M. Reproductive health and rheumatoid arthritis. BMC Rheumatol. 2024;8:53.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCao C, et al. Cholesterol-induced LRP3 downregulation promotes cartilage degeneration in osteoarthritis by targeting Syndecan-4. Nat Commun. 2022;13:7139.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSherwani Y, Al-Ezzi S, Thambidorai S. Impact of Elevated Low-Density Lipoprotein and the Risk of Acute Coronary Syndrome in Rheumatoid Arthritis: A Retrospective Study. Cureus. 2025;17:e80430.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYan Y, et al. The association between remnant cholesterol and rheumatoid arthritis: insights from a large population study. Lipids Health Dis. 2024;23:38.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChoudhury C, Sahib A, Karmakar P, Kar S. Correlation of Serum Vitamin D and High-Density Lipoprotein (HDL) Cholesterol Levels With Disease Activity in Rheumatoid Arthritis: A Single-Center Experience From Eastern India. \u003cem\u003eCureus\u003c/em\u003e 16, e69333 (2024).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGiacaglia MB et al. The Composition of the HDL Particle and Its Capacity to Remove Cellular Cholesterol Are Associated with a Reduced Risk of Developing Active Inflammatory Rheumatoid Arthritis. Int J Mol Sci 25(2024).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiberis A, Petousis S, Tsikouras P. Lipid Disorders in Pregnancy. Curr Pharm Design. 2021;27:3804\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBar A, et al. Pregnancy and postpartum dynamics revealed by millions of lab tests. Sci Adv. 2025;11:eadr7922.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhu Y, et al. Elevated serum cholesterol levels during pregnancy as predictors for postpartum hypercholesterolemia: A prospective cohort study. Int J Gynaecol Obstet. 2025;168:800\u0026ndash;11.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJones PAT, et al. Impact of postpartum physical activity on cardiometabolic health, breastfeeding, injury and infant growth and development: a systematic review and meta-analysis. Br J Sports Med. 2025;59:539\u0026ndash;49.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAgbaje AO. Associations of Sedentary Time and Physical Activity From Childhood With Lipids: A 13-Year Mediation and Temporal Study. J Clin Endocrinol Metab. 2024;109:e1494\u0026ndash;505.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBarone Gibbs B et al. ,\u003cem\u003e. Physical Activity as a Critical Component of First-Line Treatment for Elevated Blood Pressure or Cholesterol: Who, What, and How? A Scientific Statement From the American Heart Association. Hypertension (Dallas, Tex.: 1979) 78, e26-e37 (2021).\u003c/em\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFang J, Alderman MH. Serum uric acid and cardiovascular mortality the NHANES I epidemiologic follow-up study, 1971\u0026ndash;1992. National Health and Nutrition Examination Survey. JAMA. 2000;283:2404\u0026ndash;10.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlderman MH, Cohen H, Madhavan S. Dietary sodium intake and mortality: the National Health and Nutrition Examination Survey (NHANES I). Lancet (London England). 1998;351:781\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZeng CM, He J, Wang DC, Xie H. Association between triglyceride levels and rheumatoid arthritis prevalence in women: a cross-sectional study of NHANES (1999\u0026ndash;2018). BMC Womens Health. 2025;25:129.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen Z, et al. Association between remnant cholesterol (RC) and endometriosis: a cross-sectional study based on NHANES data. Lipids Health Dis. 2025;24:2.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eQian S, et al. Remnant Cholesterol and Common Carotid Artery Intima-Media Thickness in Patients With Ischemic Stroke. Circ Cardiovasc Imaging. 2021;14:e010953.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDang K, et al. The association between triglyceride-glucose index and its combination with obesity indicators and cardiovascular disease: NHANES 2003\u0026ndash;2018. Cardiovasc Diabetol. 2024;23:8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGuo HJ, Ye YL, Gao YF, Liu ZH. Age at first birth is associated with the likelihood of frailty in middle-aged and older women: A population-based analysis from NHANES 1999\u0026ndash;2018. Maturitas. 2024;181:107904.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen HL, et al. The association between the neutrophil-to-lymphocyte ratio and type 2 diabetes mellitus: a cross-sectional study. BMC Endocr disorders. 2024;24:107.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLui DTW, et al. The association of HDL-cholesterol levels with incident major adverse cardiovascular events and mortality in 0.6 million individuals with type 2 diabetes: a population-based retrospective cohort study. BMC Med. 2024;22:586.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNieman DC, Wentz LM. The compelling link between physical activity and the body's defense system. J sport health Sci. 2019;8:201\u0026ndash;17.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStanton KM, et al. Moderate- and High-Intensity Exercise Improves Lipoprotein Profile and Cholesterol Efflux Capacity in Healthy Young Men. J Am Heart Association. 2022;11:e023386.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSurgeon General's report on physical activity and health. Centers Disease Control Prev Jama. 1996;276:522.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"childbirth, pregnancy, arthritis, lipid, cholesterol, physical activity","lastPublishedDoi":"10.21203/rs.3.rs-6597672/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6597672/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eOBJECTIVE\u003c/h2\u003e \u003cp\u003eTo investigate the association between childbirth and arthritis, with a focus on the mediating effect of blood lipid indexes and protective role of physical Activity.\u003c/p\u003e\u003ch2\u003eMETHODS\u003c/h2\u003e \u003cp\u003eThe cross-sectional study utilized data from the National Health and Nutrition Examination Survey (NHANES) from 2007 to 2020. Blood lipid indexes were included triglyceride, total cholesterol (TC), LDL-cholesterol (LDL-C) and HDL-cholesterol (HDL-C, mmol/L). Then, remnant cholesterol (RC) was calculated.\u003c/p\u003e\u003ch2\u003eRESULTS\u003c/h2\u003e \u003cp\u003eA total of 6491 participants were included in this study, 2144 (33.03%) women occurred arthritis. Compared to never pregnancy women, the rates of arthritis in the participants with had childbirth were significantly increase (36.03% vs 17.94%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). After adjusted, the risk of arthritis for the women had childbirth was significantly increased (OR\u0026thinsp;=\u0026thinsp;4.17, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). In addition, the birth number and birth interval cycle would increase the risk of arthritis caused by childbirth experience. There was a nonlinear (L-shaped) relationship were observed in blood triglyceride and RC (p for nonlinearity\u0026thinsp;\u0026lt;\u0026thinsp;.001). Mediation analysis demonstrated that blood RC accounted for 8.45% of observed association between childbirth and arthritis (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). RC was the highest WQS weigh among four cholesterols, with the highest contributions 0.63. There was a nonlinear (U-shaped) relationship between vigorous recreational activities and the risk of arthritis (p for nonlinearity\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\u003ch2\u003eCONCLUSIONS\u003c/h2\u003e \u003cp\u003eChildbirth history is a significant yet underrecognized risk factor for arthritis in women, mediated in part by persistent lipid abnormalities, particularly elevated RC, while physical activity offers protective benefits.\u003c/p\u003e","manuscriptTitle":"Childbirth History Increases Arthritis Risk in Women: The Role of Lipid Metabolism and Physical Activity","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-14 11:50:04","doi":"10.21203/rs.3.rs-6597672/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":"07382e19-079a-424c-b62d-2e44d5bd84e7","owner":[],"postedDate":"May 14th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-05-27T06:38:49+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-14 11:50:04","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6597672","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6597672","identity":"rs-6597672","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}