Association between Parkinson's disease and cardiovascular disease mortality: A prospective population-based study from NHANES

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Therefore, it is critical to examine the association between PD and CVD mortality specifically in the US population. Methods In this cohort investigation, we enrolled 28,242 participants from the NHANES spanning from 2003 to 2018. The 380 cases of PD in the cohort were identified by documenting "ANTIPARKINSON AGENTS" in their reported prescription medications. Mortality outcomes were ascertained by cross-referencing the cohort database with the National Death Index, which was last updated on 31 December 2019. Cardiovascular disease (CVD) mortality was categorised according to the 10th revision of the International Classification of Diseases using a spectrum of diagnostic codes. Weighted multivariable Cox regression analysis was used to examine the association between PD and the risk of CVD mortality. Results Among 28242 adults included in the study (mean age, 60.156 (12.55) years, 13766 men (48.74%) ), median follow-up period was 89 months. Individuals with PD had an adjusted HR of 1.82 (95% CI, 1.24–2.69; p = 0.002) for CVD mortality and 1.84 (95% CI, 1.44–2.33; p < 0.001) for all-cause mortality compared to those without PD. The association between PD and CVD mortality was robust in sensitivity analyses, after excluding participants who died within 2 years of follow-up and those with a history of cancer at baseline (HR,1.82 (95% CI, 1.20–2.75; p = 0.005). Conclusions Parkinson's disease was associated with a higher long-term CVD mortality rate in the US population. NHANES cardiovascular disease mortality Parkinson's disease Figures Figure 1 Figure 2 Introduction Parkinson's disease (PD) is a sophisticated and progressively worsening neurodegenerative condition, marked by symptoms such as tremors, muscle stiffness, reduced mobility, and impaired balance. These manifestations stem from the ongoing degeneration of neurons within the brain[ 1 ]. Parkinson's disease (PD) is relatively rare in individuals under the age of 50, as life expectancy increases, the prevalence and burden of PD increase worldwide.In developed countries, PD accounts for about 0.3% of ordinary adults, and the incidence rate is 8–18 cases per 100000 person years[ 2 ] .Even by 2030, the increase in PD will be in excess of 50%[ 3 ]. Although epidemiologic studies have consistently reported that Parkinson's disease is associated with higher premature mortality rates compared to the general population[ 4 ][ 5 ][ 6 ], but the association between PD and cardiovasculardiseases(CVDs) remains uncertain. In the United States, CVDs like myocardial infarction(MI), ischemic stroke, and congestive heart failure(CHF) account for over 25% of deaths[ 7 ]. Therefore, exploring the relationship between PD and CVD mortality among adult Americans is very important. In this study, we utilized a substantial cohort with extensive, long-term follow-up data from the National Health and Nutrition Examination Survey (NHANES) to evaluate cardiovascular disease (CVD) mortality rates and overall mortality rates among individuals with Parkinson's disease (PD). METHODS Study population From 2003 to 2018, a cumulative total of 80, 312 participants took part in the National Health and Nutrition study (NHANES)(Fig. 1 ). Participants younger than 40 years were not included in the study due to the epidemiological features of Parkinson's Disease(PD). Statistical analysis was conducted on a cohort of 28,242 participants, including 380 individuals diagnosed with Parkinson's disease and 27,862 individuals without the condition. Participants with missing data and loss to follow-up were excluded from the analysis. The complete data integration process is illustrated in Fig. 1 . The National Center for Health Statistics (NCHS) conducts the National Health and Nutrition study (NHANES), a nationally representative study, with the goal of evaluating the health or nutritionalstate of the US population that is not institutionalized. Utilizing a multistage, stratified probability sampling strategy, NHANES collects demographic and detailed health information through home visits, screening, and laboratory testing,by a mobile exam center. The NCHS Research Ethics Review Board approved the NHANES study protocol, and participants provided written informed permission at enrollment (source: https://www.cdc.gov/nchs/nhanes/irba98.htm ). The Suining Central Hospital institutional review board deemed the study exempt due to its utilization of publicly accessible, deidentified data, thus waiving the requirement for informed consent. Adhering to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines, the study maintained a high standard of reporting quality.This cohort study utilized data from adult participants aged 40 years and older in the NHANES cycles from 2003 to 2018. Exclusion criteria included loss to follow-up and missing data on mPD. Participant enrollment procedure is illustrated in Fig. 1 . Assessment of Parkinson's disease and mortality In the NHANES database, participants with Parkinson’s disease were identified by the presence of "ANTIPARKINSON AGENTS" in their prescription medication responses, in line with previous literature[ 8 ][ 9 ][ 10 ]. To be classified as having Parkinson’s disease, individuals had to be receiving treatment for it due to limitations in NHANES medications and codes. Others were categorized as non-Parkinson’s disease participants.Mortality data was collected by linking the cohort database to the Centers for Disease Control's National Death Index as of December 31, 2019. Cardiovascular mortality in this analysis encompasses a range of ICD codes, specifically: I00–I09 for acute rheumatic fever and chronic rheumatic heart conditions; I11 for hypertensive heart disease; I13 for combined hypertensive heart and renal disease; I20–I25 for ischemic heart diseases; I26–I28 for pulmonary embolism and other acute pulmonary heart conditions; I29 for a variety of cardiovascular diseases due to diverse causes; I30–I51 for additional forms of heart disease; and I60–I69 for cerebrovascular disorders. Assessment of covariates Based on previous studies, the potential covariates included age, gen der, marital status, race/ethnicity, education level, family income, body mass index (BMI), smoking status, alcohol drinking status, diabetes and hypertension[ 11 ][ 12 ]. Race/ethnicity was classified as non-Hispanic white, non-Hispanic black, Mexican American, or other. Marital status was defined as married, living with a partner, or living alone. Educational attainment was divided into three categories: fewer than nine years, nine to twelve years, and more than twelve years. According to a US government report, family income is divided into three categories based on the poverty income ratio (PIR): low (PIR ≤ 1.3), medium (PIR > 1.3 to 3.5), and high (PIR > 3.5). The smoking status was classified as: never smokers (smoked fewer than 100 cigarettes), current smokers.The classification of alcohol consumption included the categories of "never" (having never consumed alcohol in their lifetime), "former" (having previously consumed alcohol but no longer do), "heavy" alcohol use (≥ 3 drinks daily for women, ≥ 4 drinks daily for men, or binge drinking [≥ 4 drinks in one occasion for women, ≥ 5 drinks in one occasion for men] on 5 or more days in a month), "moderate" alcohol use (≥ 2 drinks daily for women, ≥ 3 drinks daily for men, or binge drinking on ≥ 2 days in a month, or a history of daily binge drinking), and "mild" alcohol use (not meeting the criteria mentioned above)[ 13 ]. Physical activity(PA) is defined as the time individuals spend engaging in activities such as walking, biking, household chores, work-related tasks, and recreational pursuits throughout the week, if there is no exercise this week, the exercise time is 0, which is redefined as 0. Previous diseases, including hypertension, diabetes, stroke, and coronary heart disease, were identified through participants' responses to the questionnaire regarding whether a doctor had been notified of these conditions in the past. Statistical analysis This study conducted a secondary analysis of publicly available data from the NHANES dataset. It is important to utilize sampling weights and design variables in all analyses to avoid biased estimates and inflated significance levels. Therefore, our analysis followed NHANES guidelines by incorporating a complex sampling design and sampling weights[ 14 ]. Our research data is derived from family interviews and Mobile Examination Center (MEC) data collected during NHANES surveys. As per the NHANES survey sample weight analysis guidelines, it is recommended to utilize the weights provided by MEC. The calculation method for sampling weight involves taking the MEC weight for each participant and multiplying it by 1/8 x 2 years, spanning from 2003 to 2018. The National Death Index is updated every 4 years and the latest follow-up data is currently available as of December 31, 2019. Therefore, the follow-up period for each participant was calculated from the date of testing at the MEC to the date of death or the end of follow-up on December 31, 2019. All analyses were performed using the statistical software packages R4.3.3( http://www.R-project.org ) and Free Statistics software version 1.9.2. Due to the small percentage of missing data for all variables in this study (missing rates ranged from 0–9%),we employed a multivariate single imputation method using an iterative imputer with a Bayesian Ridge model as the estimator at each imputation step, following the approach proposed by van Buuren & Groothuis-Oudshoorn (2011). Categorical and continuous variables were presented as unweighted percentages and means (standard deviation [SD]), respectively. The study utilized linear regression analyses and chi-square tests to compare continuous and categorical variables, respectively. A weighted, multivariable Cox proportional hazards regression models were employed to assess the hazard ratio (HR) and 95% confidence interval (95% CI) for the relationship between PD and the risks of CVD and all-cause mortality. Model 1 was adjusted for age, sex, marital status, race/ethnicity, education level, family income, and NHANES cycle. Model 2 included additional adjustments for smoking status, alcohol drinking status, and physical activity. Finally, Model 3 further adjusted for BMI, diabetes, and hypertension[ 11 ][ 12 ]. Sensitivity analyses were performed to assess the reliability of our findings. To mitigate the risk of reverse causality, individuals who passed away within 2 years of recruitment were excluded. Additionally, participants with cancer were also excluded to prevent any potential impact on the mortality rate[ 15 ]. RESULTS Study population Between 2003 and 2018, a total of 80,312 participants were involved in the NHANES study (Fig. 1 ). Participants under 40 years of age were excluded based on the epidemiological characteristics of Parkinson's Disease (PD). After removing participants with missing data on Parkinson's data and loss to follow-up, statistical analysis was performed on 28242 participants,which included 380 participants with PD and 27862 participants without PD. The complete process of data integration is illustrated in Figure.1. Baseline characteristics At baseline, 380 participants had Parkinson's disease, whereas 27862 did not. Table 1 shows the baseline characteristics of the 28242 study participants. The mean age of the participants was 60.1 (12.5) years, 13766 (48.7%) were men and 14476.00 (51.2%) were women. In comparison to the 27862 individuals without PD, the 380 individuals with PD were more likely to be older (60.092(12.539)years vs. 64.829 (12.955)years, respectively),have a higher BMI (30.566 (7.422) kg/m2 vs 29.382 (6.666), respectively), and they were more likely to have a higher prevalence rate of diabetes (17090.00 (25.47%) vs.128.00 (33.68%), respectively) and hypertension(15736.00 (56.49%) vs 259.00 (68.16%),respectively). Table 1 Baseline characteristics of participants in the NHANES 2003–2018 cycles. Participants a Overall no parkinson parkinson p Characteristic n = 28242 n = 27862 n = 380 Age 60.156 (12.556) 60.092 (12.539) 64.829 (12.955) < 0.0001 Sex male 13766.00 (48.74) 13589.00 (48.77) 177.00 (46.58) 0.3955 female 14476.00 (51.26) 14273.00 (51.23) 203.00 (53.42) Race Non-Hispanic White 12763.00 (45.19) 12515.00 (44.92) 248.00 (65.26) < 0.0001 Non-Hispanic Black 6107.00 (21.62) 6052.00 (21.72) 55.00 (14.47) Mexican American 4163.00 (14.74) 4126.00 (14.81) 37.00 ( 9.74) other 5209.00 (18.44) 5169.00 (18.55) 40.00 (10.53) Marital married or living with partners 17361.00 (61.51) 17164.00 (61.64) 197.00 (51.84) 0.0001 living alone 10863.00 (38.49) 10680.00 (38.36) 183.00 (48.16) PIR ≤ 1.30 7566.00 (29.50) 7432.00 (29.37) 134.00 (38.95) 3.50 8273.00 (32.26) 8199.00 (32.41) 74.00 (21.51) Education Less than high school 8008.00 (28.40) 7883.00 (28.34) 125.00 (32.89) 0.1305 High school or equivalent 6555.00 (23.25) 6476.00 (23.28) 79.00 (20.79) Above high school 13635.00 (48.35) 13459.00 (48.38) 176.00 (46.32) Smoke never 14457.00 (51.23) 14280.00 (51.29) 177.00 (46.70) 0.0809 former 8518.00 (30.18) 8402.00 (30.18) 116.00 (30.61) now 5247.00 (18.59) 5161.00 (18.54) 86.00 (22.69) Alcohol never 3850.00 (15.47) 3802.00 (15.48) 48.00 (15.00) < 0.0001 former 5422.00 (21.79) 5319.00 (21.66) 103.00 (32.19) mild 8929.00 (35.89) 8814.00 (35.89) 115.00 (35.94) moderate 3257.00 (13.09) 3232.00 (13.16) 25.00 ( 7.81) heavy 3422.00 (13.75) 3393.00 (13.82) 29.00 ( 9.06) Physical activity, min/week 583.959 (1202.836) 587.545 (1206.582) 321.061 (846.774) < 0.0001 BMI/kg.m2 29.398 (6.678) 29.382 (6.666) 30.566 (7.422) 0.0027 Hypertension no 12241.00 (43.35) 12120.00 (43.51) 121.00 (31.84) < 0.0001 yes 15995.00 (56.65) 15736.00 (56.49) 259.00 (68.16) Diabetes no 21001.00 (74.42) 20749.00 (74.53) 252.00 (66.32) 0.0003 yes 7218.00 (25.58) 7090.00 (25.47) 128.00 (33.68) Table 2 Hazard ratios of CVD and all-cause mortality by Parkinson's disease among adults in NHANES 2003–2018 Deaths, no./total no. Without parkinson With parkinson HR (95% CI) P_value All-cause mortality Crude model 5133/27862 135/380 2.44(1.84, 3.25) < 0.001 Mode 1 5133/27862 135/380 1.84(1.43, 2.37) < 0.001 Model 2 5133/27862 135/380 1.85(1.47, 2.33) < 0.001 Model 3 5133/27862 135/380 1.84(1.44, 2.33) < 0.001 CVD mortality Crude model 1616/27862 42/380 2.44(1.97,4.11) < 0.001 Mode 1 1616/27862 42/380 1.95(1.32,2.89) < 0.001 Model 2 1616/27862 42/380 1.87(1.27.2.73) < 0.001 Model 3 1616/27862 42/380 1.82(1.24,2.69) 0.002 Model1:Adjusted for age, sex, marital status, race/ethnicity, education level, family income, and NHANES cycle. Model2:Further adjusted for smoking status,Physical activity and alcohol drinking status. Model3:Further adjusted for BMI, hypertension,diabetes Table 3 Sensitivity analyses,Exclude cancer and who died within 2 years of follow-up Deaths, no./total no. Without parkinson With parkinson HR (95% CI) P_value All-cause mortality Crude model 3273/22705 82/273 2.44(1.84, 3.25) < 0.001 Mode 1 3273/22705 82/273 1.84(1.43, 2.37) < 0.001 Model 2 3273/22705 82/273 1.73(1.36, 2.20) < 0.001 Model 3 3273/22705 82/273 1.77(1.38, 2.26) < 0.001 CVD mortality Crude model 1069/22705 30/273 2.71(1.80,4.08) < 0.001 Mode 1 1069/22705 30/273 1.91(1.23,2.95) 0.004 Model 2 1069/22705 30/273 1.77(1.17.2.68) 0.007 Model 3 1069/22705 30/273 1.82(1.20,2.75) 0.005 Model1:Adjusted for age, sex, marital status, race/ethnicity, education level, family income, and NHANES cycle. Model2:Further adjusted for smoking status,Physical activity and alcohol drinking status. Model3:Further adjusted for BMI, hypertension,diabetes a Data are presented as unweighted number for categorical variables(percentage) and continuous variables(mean (standard error)). Discussion This cohort study's findings indicate that Parkinson's disease (PD) elevates the risk of both cardiovascular disease (CVD) mortality and overall mortality. The robustness of these results was confirmed through subgroup and sensitivity analyses. Our findings on overall mortality rate are consistent with previous research findings.A historical cohort study spanning 11 years revealed a mortality rate of 1.64 (95% CI: 1.21-2.23) among patients with Parkinson's disease compared to the control group[16]. Similarly, the Sydney and Netherlands multicenter study reported a higher mortality rate in individuals with Parkinson's Disease (PD) compared to population data[17][18]. A meta-analysis concluded that cognitive impairment/dementia, ageing, late age of onset, male and gait disturbance are risk factors for mortality in PD patients[19]. The literature on cardiovascular disease mortality in people with PD is still limited and controversial. A previous study showed that the risk of ischemic heart disease and in Parkinson's disease patients remains unchanged compared to the general population (HR 1.1, 95% CI 0.6-2.0)[20]. Even some studies suggested that people with Parkinson's disease have a reduced overall incidence of both ischaemic stroke and heart attack[21][22]. However, previous studies have demonstrated that individuals with Parkinson's disease (PD) may encounter autonomic dysfunction, cardiomyopathy, coronary heart disease, arrhythmia, or sudden cardiac death (SCD), resulting in a higher prevalence of heart failure among PD patients[23][24]. In a recent study by Park et al[11]. in South Korea, a nationwide cohort analysis revealed that individuals with Parkinson's disease may face a greater probability of experiencing cardiovascular events and death compared to those without the condition，it was found that individuals with Parkinson's disease (PD) had a higher risk of myocardial infarction (HR 1.43 ,95% CI:1.28-1.59), ischemic stroke (HR 1.42,95% CI:1.31-1.54]), congestive heart failure (HR 1.65 ,95% CI:1.52-1.78). Our research findings also indicate that the cardiovascular mortality rate among Parkinson's patients is higher compared to non-Parkinson's patients.By utilizing a substantial sample size of American participants, our study contributes to enhancing the overall applicability of these results. Autonomic dysfunction is frequently observed in Parkinson's disease (PD) and can manifest in the autonomic nervous system, including the heart[25]. In a study conducted on the heart tissue of Parkinson's disease patients in Japan, it was discovered that 9 out of 11 patients had Lewy bodies present in both tyrosine hydroxylase positive and negative neural processes, this suggests that the postganglionic sympathetic nervous system and intrinsic neurons in the heart play a role in the development of Parkinson's disease[26]. A prospective study conducted in Sweden revealed that diabetes and elevated fasting blood glucose levels were identified as risk factors for Parkinson's disease (PD). The study also found that a higher neutrophil to lymphocyte ratio (NLR) in the general population was linked to an increased risk of PD. Interestingly, diabetes, fasting glucose, and NLR are all associated with the risk of coronary events or ischemic stroke[12]. So,it is increasingly recognised that PD patients can develop coronary heart disease and ischemic stroke.Then,most Parkinson's disease patients receive levodopa treatment, which has been shown to increase homocysteine levels in the blood,elevated homocysteine levels have been associated with a higher incidence of cerebrovascular and cardiovascular diseases[19]. Some study also suggest that the relationship between Parkinson's disease and cardiovascular disease is complex, with overlapping biological mechanisms, including inflammation, insulin resistance, lipid metabolism, and oxidative stress[27]. These scientific discoveries corroborate our study's perspective, suggesting that Parkinson's disease (PD) increases the likelihood of mortality associated with cardiovascular disease (CVD). In our stratified analysis, we identified several factors that influence the association between PD and cardiovascular disease mortality, such as older age, Non-Hispanic White,male, lower BMI, never smoking, and past or current alcohol consumption.Similar to a South Korea study found a negative dose-response relationship between BMI at diagnosis and mortality in patients with Parkinson's disease (PD), a 10% change in BMI was significantly linked to mortality outcomes[28]. One possible explanation for this negative correlation is that higher BMI affects insulin levels, which may play a beneficial role in dopaminergic neurodegeneration[29]. we identified a significant interaction regarding cardiovascular disease mortality among individuals with Parkinson's disease, distinguishing between the male and female subgroups.A retrospective study has analyzed the trend of Parkinson's disease (PD) mortality revealed that males had a mortality rate for PD that was twice as high as females[30]. The gender disparity in Parkinson's disease development could be attributed to the potential neuroprotective effect of female gonadotropins, especially circulating estradiol, on the dopaminergic system. Research indicates that men typically acquire Parkinson's disease at a younger age than women, leading to a higher mortality rate in men at an earlier stage, which may counterbalance other risk factors[31]. In the United States, there exists racial and ethnic disparities in access to neurological care, with black and Hispanic patients being less likely than white patients to consult outpatient neurologists. This discrepancy suggests that white patients have a greater likelihood of being diagnosed with Parkinson's disease[32], possibly attributed to their overall higher socioeconomic status in terms of education and income compared to minority populations. Consequently, this disparity may contribute to the higher cardiovascular disease mortality rates in white individuals with PD in comparison to other racial and ethnic groups.Numerous clinical studies have demonstrated a negative correlation between smoking and the occurrence of Parkinson's disease in both genders[33][34]. Smoking might have a protective effect against Parkinson's disease; however, the cause of the higher vulnerability to cardiovascular disease mortality in Parkinson's disease patients who have never smoked remains unclear. Study strengths and limitations This study is the first to examine cardiovascular disease mortality in Parkinson's disease patients using data from the NHANES. The sample size was both large and representative, allowing for a more comprehensive analysis. However there were some limitations to this study. Initially, it is critical to note that the determination of Parkinson's disease (PD) within our research was reliant on participants' self-reported medication usage, without corroboration through a formal medical diagnosis. This approach acknowledges the possibility that a subset of participants may be either unaware of their PD status or may exhibit milder symptoms not necessitating pharmacological intervention, potentially leading to an underrepresented sample.Moreover, we are mindful that patients with tremor-associated neurological conditions other than PD might be prescribed antiparkinsonian medications, yet lack a definitive PD diagnosis. Such instances could precipitate misclassification within our study, thereby introducing a bias into our research outcomes.To address these limitations, future investigations should endeavor to adopt more rigorous diagnostic methodologies. This might entail comprehensive clinical evaluations by specialists in movement disorders or the employment of standardized diagnostic instruments. By integrating these refined diagnostic practices, the accuracy of PD case identification can be enhanced, thereby mitigating the risk of misclassification. Conclusions This large cohort study suggests that individuals with Parkinson's disease (PD) have a higher risk of cardiovascular disease (CVD) mortality compared to those without PD. The association appears to be stronger in older age, Non-Hispanic White individuals, males, those with lower BMI, non-smokers, and those who currently or previously consumed alcohol. Future research should delve deeper into the biological mechanisms underlying this relationship to develop effective strategies for reducing CVD mortality in individuals with PD. Declarations Acknowledgements The authors thank the NHANES staff, investigators, and participants. We thank Dr Liu Jie (People's Liberation Army of China General Hospital, Beijing, China) for assistance with this revision. Authors’ contributions Li Ke wrote the first draft of the manuscript. All authors performed the conceptualization, methods, data collection and analysis, commented on previous versions of the manuscript, contributed to the study conception and design, and read and approved the final manuscript. Funding This work has not received any specific grant from any funding in the public, commercial or not-for-profit sectors. Conflict of interest The authors declare that the research was carried out without any without any commercial or financial relationship that could be construed as a potential that could be construed as a potential conflict of interest. Ethics approval The NHANES obtained approval from the National Center for Health Statistics Research Ethics Review Board and was performed in accordance with the ethical standards as laid down in the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards. Data availability The data that support the findings of this study are openly available in [NHANES] at [https://www.cdc.gov/nchs/nhanes/index.htm]. Consent for publication Not applicable. References Dexter DT, Jenner P. Parkinson disease: from pathology to molecular disease mechanisms. Free Radic Biol Med. 2013;62:132–44. https://doi.org/10.1016/j.freeradbiomed.2013.01.018 . Fan HC, Chen SJ, Harn HJ, Lin SZ. Parkinson's disease: from genetics to treatments. Cell Transpl. 2013;22(4):639–52. https://doi.org/10.1016/j.freeradbiomed.2013.01.018 . Kalia LV, Lang AE. Parkinson's disease. Lancet. 2015;386(9996):896–912. https://doi.org/10.1016/S0140-6736(14)61393-3 . Dobkin BH. 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Lewy body-type degeneration in cardiac plexus in Parkinson's and incidental Lewy body diseases. Neurology. 1999;52(6):1269–71. https://doi.org/10.1212/WNL.52.6.1269 . Potashkin J, Huang X, Becker C, Chen H, Foltynie T, Marras C. Understanding the links between cardiovascular disease and Parkinson's disease. Mov Disord. 2020;35(1):55–74. https://doi.org/10.1002/mds.27836 . Yoon SY, Heo SJ, Lee HJ, Shin J, Kim YW, Yang SN, Park YG. Initial BMI and Weight Loss over Time Predict Mortality in Parkinson Disease. J Am Med Dir Assoc. 2022;23(10):1719. .e1-1719.e7. Craft S, Watson GS. Insulin and neurodegenerative disease: shared and specific mechanisms. Lancet Neurol. 2004;3(3):169–78. https://doi.org/10.1016/S1474-4422(04)00681-7 . Rong S, Xu G, Liu B, Sun Y, Snetselaar LG, Wallace RB, Li B, Liao J, Bao W. Trends in Mortality From Parkinson Disease in the United States, 1999–2019. Neurology. 2021;97(20):e1986-e1993. https://doi.org/10.1212/WNL.0000000000012826 . Cerri S, et al. Parkinson's Disease in Women and Men: What's the Difference? J Parkinson's disease vol. 2019;9(3):501–15. https://doi.org/10.3233/JPD-191683 . Saadi A, Himmelstein DU, Woolhandler S, Mejia NI. Racial disparities in neurologic health care access and utilization in the United States. Neurology. 2017;88(24):2268–75. https://doi.org/10.1212/WNL.0000000000004025 . Hernán MA, Zhang SM, Rueda-deCastro AM, Colditz GA, Speizer FE, Ascherio A. Cigarette smoking and the incidence of Parkinson's disease in two prospective studies. Ann Neurol. 2001;50(6):780–6. https://doi.org/10.1002/ana.10028 . Gallo V, Vineis P, Cancellieri M, Chiodini P, Barker RA, Brayne C, Pearce N, Vermeulen R, Panico S, Bueno-de-Mesquita B, Vanacore N, Forsgren L, Ramat S, Ardanaz E, Arriola L, Peterson J, Hansson O, Gavrila D, Sacerdote C, Sieri S, Kühn T, Katzke VA, van der Schouw YT, Kyrozis A, Masala G, Mattiello A, Perneczky R, Middleton L, Saracci R, Riboli E. Exploring causality of the association between smoking and Parkinson's disease. Int J Epidemiol. 2019;48(3):912–25. https://doi.org/10.1093/ije/dyy230 . Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 07 Jun, 2024 Reviews received at journal 05 Jun, 2024 Reviews received at journal 29 May, 2024 Reviewers agreed at journal 23 May, 2024 Reviewers agreed at journal 23 May, 2024 Reviewers agreed at journal 21 May, 2024 Reviewers invited by journal 17 May, 2024 Editor assigned by journal 17 May, 2024 Submission checks completed at journal 17 May, 2024 First submitted to journal 09 May, 2024 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. 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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-4395199","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":307628564,"identity":"0692f5d9-46e7-4e8d-88c3-4c4728f70d66","order_by":0,"name":"Li Ke","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Li","middleName":"","lastName":"Ke","suffix":""},{"id":307628565,"identity":"ab847f6a-f491-46da-9af4-0c45f147a945","order_by":1,"name":"Lei Zhao","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Lei","middleName":"","lastName":"Zhao","suffix":""},{"id":307628566,"identity":"3d456ae4-5a3b-4c49-98ce-7f81135f125a","order_by":2,"name":"Wenli Xing","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4ElEQVRIie3RIQvCQBTA8SeDN8Oh9QTZvsJgsOSHuUNZmiJYFgyKsgXxuxiNNw8und1gmMVksRk9waZssxnuny7cj3uPA7DZ/jB0V0KwdOAhFMuSpfN60iGKi1LHYaclZVBqVU88moTFJTtwz1Fx77J2GgxGk0AwLRiijlK+QOjmG1ZNyHVqdjlPkOjoxPd9oPq4qybucGdeuc6QvohGCOi4hgALBM8kz/xbNOWZ04C0R28CKoZmhChmBotDBCkp04rU7uLnK3l/mK/0F8XSHOZeN99Wk4/Ib9dtNpvN9rUnuCxVFonyIq0AAAAASUVORK5CYII=","orcid":"","institution":"","correspondingAuthor":true,"prefix":"","firstName":"Wenli","middleName":"","lastName":"Xing","suffix":""}],"badges":[],"createdAt":"2024-05-09 12:40:46","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4395199/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4395199/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":57629170,"identity":"ad2de25e-86ab-48d6-aa76-3ccb36bcc41f","added_by":"auto","created_at":"2024-06-03 14:35:55","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":161878,"visible":true,"origin":"","legend":"\u003cp\u003eStudy flow chart.\u003c/p\u003e","description":"","filename":"Figure1Studyflowchart.png","url":"https://assets-eu.researchsquare.com/files/rs-4395199/v1/da9f4aac40523300574c4d64.png"},{"id":57629171,"identity":"596495b7-4bb6-4d5a-8530-396d8ce19df1","added_by":"auto","created_at":"2024-06-03 14:35:55","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":320293,"visible":true,"origin":"","legend":"\u003cp\u003eAssociation between Parkinson's disease and CVD mortality according to general characteristics. The stratifications were adjusted for all variables (education level, marital status, family income, NHANES cycle, physical activity,hypertension and diabetes except for the stratification factor itself. Squares represent the HRs and horizontal lines represent 95% CIs. Diamonds represent the overall HR, and the outer points of the diamonds represent the 95% CI. BMI, body mass index; CI, confidence interval; CVD, cardiovascular disease; HR, hazard ratio.\u003c/p\u003e","description":"","filename":"Figure2forest.png","url":"https://assets-eu.researchsquare.com/files/rs-4395199/v1/da07c893abd2b207a9ce90d2.png"},{"id":57629172,"identity":"8108a5ce-6e22-4b31-9738-e878769e9274","added_by":"auto","created_at":"2024-06-03 14:36:00","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":995014,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4395199/v1/060dbd74-9005-4581-a419-d4728949b830.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Association between Parkinson's disease and cardiovascular disease mortality: A prospective population-based study from NHANES","fulltext":[{"header":"Introduction","content":"\u003cp\u003eParkinson's disease (PD) is a sophisticated and progressively worsening neurodegenerative condition, marked by symptoms such as tremors, muscle stiffness, reduced mobility, and impaired balance. These manifestations stem from the ongoing degeneration of neurons within the brain[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Parkinson's disease (PD) is relatively rare in individuals under the age of 50, as life expectancy increases, the prevalence and burden of PD increase worldwide.In developed countries, PD accounts for about 0.3% of ordinary adults, and the incidence rate is 8\u0026ndash;18 cases per 100000 person years[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e] .Even by 2030, the increase in PD will be in excess of 50%[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAlthough epidemiologic studies have consistently reported that Parkinson's disease is associated with higher premature mortality rates compared to the general population[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e][\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e][\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], but the association between PD and cardiovasculardiseases(CVDs) remains uncertain. In the United States, CVDs like myocardial infarction(MI), ischemic stroke, and congestive heart failure(CHF) account for over 25% of deaths[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Therefore, exploring the relationship between PD and CVD mortality among adult Americans is very important.\u003c/p\u003e \u003cp\u003eIn this study, we utilized a substantial cohort with extensive, long-term follow-up data from the National Health and Nutrition Examination Survey (NHANES) to evaluate cardiovascular disease (CVD) mortality rates and overall mortality rates among individuals with Parkinson's disease (PD).\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy population\u003c/h2\u003e \u003cp\u003eFrom 2003 to 2018, a cumulative total of 80, 312 participants took part in the National Health and Nutrition study (NHANES)(Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Participants younger than 40 years were not included in the study due to the epidemiological features of Parkinson's Disease(PD). Statistical analysis was conducted on a cohort of 28,242 participants, including 380 individuals diagnosed with Parkinson's disease and 27,862 individuals without the condition. Participants with missing data and loss to follow-up were excluded from the analysis. The complete data integration process is illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eThe National Center for Health Statistics (NCHS) conducts the National Health and Nutrition study (NHANES), a nationally representative study, with the goal of evaluating the health or nutritionalstate of the US population that is not institutionalized. Utilizing a multistage, stratified probability sampling strategy, NHANES collects demographic and detailed health information through home visits, screening, and laboratory testing,by a mobile exam center. The NCHS Research Ethics Review Board approved the NHANES study protocol, and participants provided written informed permission at enrollment (source: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.cdc.gov/nchs/nhanes/irba98.htm\u003c/span\u003e\u003cspan address=\"https://www.cdc.gov/nchs/nhanes/irba98.htm\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The Suining Central Hospital institutional review board deemed the study exempt due to its utilization of publicly accessible, deidentified data, thus waiving the requirement for informed consent. Adhering to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines, the study maintained a high standard of reporting quality.This cohort study utilized data from adult participants aged 40 years and older in the NHANES cycles from 2003 to 2018. Exclusion criteria included loss to follow-up and missing data on mPD. Participant enrollment procedure is illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eAssessment of Parkinson's disease and mortality\u003c/h2\u003e \u003cp\u003eIn the NHANES database, participants with Parkinson\u0026rsquo;s disease were identified by the presence of \"ANTIPARKINSON AGENTS\" in their prescription medication responses, in line with previous literature[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e][\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e][\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. To be classified as having Parkinson\u0026rsquo;s disease, individuals had to be receiving treatment for it due to limitations in NHANES medications and codes. Others were categorized as non-Parkinson\u0026rsquo;s disease participants.Mortality data was collected by linking the cohort database to the Centers for Disease Control's National Death Index as of December 31, 2019. Cardiovascular mortality in this analysis encompasses a range of ICD codes, specifically: I00\u0026ndash;I09 for acute rheumatic fever and chronic rheumatic heart conditions; I11 for hypertensive heart disease; I13 for combined hypertensive heart and renal disease; I20\u0026ndash;I25 for ischemic heart diseases; I26\u0026ndash;I28 for pulmonary embolism and other acute pulmonary heart conditions; I29 for a variety of cardiovascular diseases due to diverse causes; I30\u0026ndash;I51 for additional forms of heart disease; and I60\u0026ndash;I69 for cerebrovascular disorders.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eAssessment of covariates\u003c/h2\u003e \u003cp\u003eBased on previous studies, the potential covariates included age, gen der, marital status, race/ethnicity, education level, family income, body mass index (BMI), smoking status, alcohol drinking status, diabetes and hypertension[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e][\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Race/ethnicity was classified as non-Hispanic white, non-Hispanic black, Mexican American, or other. Marital status was defined as married, living with a partner, or living alone. Educational attainment was divided into three categories: fewer than nine years, nine to twelve years, and more than twelve years. According to a US government report, family income is divided into three categories based on the poverty income ratio (PIR): low (PIR\u0026thinsp;\u0026le;\u0026thinsp;1.3), medium (PIR\u0026thinsp;\u0026gt;\u0026thinsp;1.3 to 3.5), and high (PIR\u0026thinsp;\u0026gt;\u0026thinsp;3.5). The smoking status was classified as: never smokers (smoked fewer than 100 cigarettes), current smokers.The classification of alcohol consumption included the categories of \"never\" (having never consumed alcohol in their lifetime), \"former\" (having previously consumed alcohol but no longer do), \"heavy\" alcohol use (\u0026ge;\u0026thinsp;3 drinks daily for women, \u0026ge;\u0026thinsp;4 drinks daily for men, or binge drinking [\u0026ge;\u0026thinsp;4 drinks in one occasion for women, \u0026ge;\u0026thinsp;5 drinks in one occasion for men] on 5 or more days in a month), \"moderate\" alcohol use (\u0026ge;\u0026thinsp;2 drinks daily for women, \u0026ge;\u0026thinsp;3 drinks daily for men, or binge drinking on \u0026ge;\u0026thinsp;2 days in a month, or a history of daily binge drinking), and \"mild\" alcohol use (not meeting the criteria mentioned above)[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Physical activity(PA) is defined as the time individuals spend engaging in activities such as walking, biking, household chores, work-related tasks, and recreational pursuits throughout the week, if there is no exercise this week, the exercise time is 0, which is redefined as 0. Previous diseases, including hypertension, diabetes, stroke, and coronary heart disease, were identified through participants' responses to the questionnaire regarding whether a doctor had been notified of these conditions in the past.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eThis study conducted a secondary analysis of publicly available data from the NHANES dataset. It is important to utilize sampling weights and design variables in all analyses to avoid biased estimates and inflated significance levels. Therefore, our analysis followed NHANES guidelines by incorporating a complex sampling design and sampling weights[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Our research data is derived from family interviews and Mobile Examination Center (MEC) data collected during NHANES surveys. As per the NHANES survey sample weight analysis guidelines, it is recommended to utilize the weights provided by MEC. The calculation method for sampling weight involves taking the MEC weight for each participant and multiplying it by 1/8 x 2 years, spanning from 2003 to 2018. The National Death Index is updated every 4 years and the latest follow-up data is currently available as of December 31, 2019. Therefore, the follow-up period for each participant was calculated from the date of testing at the MEC to the date of death or the end of follow-up on December 31, 2019. All analyses were performed using the statistical software packages R4.3.3(\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.R-project.org\u003c/span\u003e\u003cspan address=\"http://www.R-project.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and Free Statistics software version 1.9.2. Due to the small percentage of missing data for all variables in this study (missing rates ranged from 0\u0026ndash;9%),we employed a multivariate single imputation method using an iterative imputer with a Bayesian Ridge model as the estimator at each imputation step, following the approach proposed by van Buuren \u0026amp; Groothuis-Oudshoorn (2011). Categorical and continuous variables were presented as unweighted percentages and means (standard deviation [SD]), respectively. The study utilized linear regression analyses and chi-square tests to compare continuous and categorical variables, respectively. A weighted, multivariable Cox proportional hazards regression models were employed to assess the hazard ratio (HR) and 95% confidence interval (95% CI) for the relationship between PD and the risks of CVD and all-cause mortality. Model 1 was adjusted for age, sex, marital status, race/ethnicity, education level, family income, and NHANES cycle. Model 2 included additional adjustments for smoking status, alcohol drinking status, and physical activity. Finally, Model 3 further adjusted for BMI, diabetes, and hypertension[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e][\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Sensitivity analyses were performed to assess the reliability of our findings. To mitigate the risk of reverse causality, individuals who passed away within 2 years of recruitment were excluded. Additionally, participants with cancer were also excluded to prevent any potential impact on the mortality rate[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStudy population\u003c/h2\u003e \u003cp\u003eBetween 2003 and 2018, a total of 80,312 participants were involved in the NHANES study (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Participants under 40 years of age were excluded based on the epidemiological characteristics of Parkinson's Disease (PD). After removing participants with missing data on Parkinson's data and loss to follow-up, statistical analysis was performed on 28242 participants,which included 380 participants with PD and 27862 participants without PD. The complete process of data integration is illustrated in Figure.1.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eBaseline characteristics\u003c/h2\u003e \u003cp\u003eAt baseline, 380 participants had Parkinson's disease, whereas 27862 did not. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the baseline characteristics of the 28242 study participants. The mean age of the participants was 60.1 (12.5) years, 13766 (48.7%) were men and 14476.00 (51.2%) were women. In comparison to the 27862 individuals without PD, the 380 individuals with PD were more likely to be older (60.092(12.539)years vs. 64.829 (12.955)years, respectively),have a higher BMI (30.566 (7.422) kg/m2 vs 29.382 (6.666), respectively), and they were more likely to have a higher prevalence rate of diabetes (17090.00 (25.47%) vs.128.00 (33.68%), respectively) and hypertension(15736.00 (56.49%) vs 259.00 (68.16%),respectively).\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\u003e\u0026emsp;Baseline characteristics of participants in the NHANES 2003\u0026ndash;2018 cycles.\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\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c6\" namest=\"c3\"\u003e \u003cp\u003eParticipants\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eno parkinson\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eparkinson\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;28242\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;27862\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;380\u003c/p\u003e \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\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60.156 (12.556)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e60.092 (12.539)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e64.829 (12.955)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13766.00 (48.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13589.00 (48.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e177.00 (46.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.3955\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003efemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14476.00 (51.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14273.00 (51.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e203.00 (53.42)\u003c/p\u003e \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\u003eRace\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNon-Hispanic White\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12763.00 (45.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12515.00 (44.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e248.00 (65.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNon-Hispanic Black\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6107.00 (21.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6052.00 (21.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e55.00 (14.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMexican American\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4163.00 (14.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4126.00 (14.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e37.00 ( 9.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eother\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5209.00 (18.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5169.00 (18.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e40.00 (10.53)\u003c/p\u003e \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\u003eMarital\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emarried or living with partners\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17361.00 (61.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17164.00 (61.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e197.00 (51.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eliving alone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10863.00 (38.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10680.00 (38.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e183.00 (48.16)\u003c/p\u003e \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\u003ePIR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;1.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7566.00 (29.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7432.00 (29.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e134.00 (38.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.31\u0026ndash;3.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9806.00 (38.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9670.00 (38.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e136.00 (39.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;3.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8273.00 (32.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8199.00 (32.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e74.00 (21.51)\u003c/p\u003e \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\u003eEducation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLess than high school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8008.00 (28.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7883.00 (28.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e125.00 (32.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.1305\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh school or equivalent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6555.00 (23.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6476.00 (23.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e79.00 (20.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAbove high school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13635.00 (48.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13459.00 (48.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e176.00 (46.32)\u003c/p\u003e \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\u003eSmoke\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003enever\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14457.00 (51.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14280.00 (51.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e177.00 (46.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.0809\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eformer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8518.00 (30.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8402.00 (30.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e116.00 (30.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003enow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5247.00 (18.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5161.00 (18.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e86.00 (22.69)\u003c/p\u003e \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\u003eAlcohol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003enever\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3850.00 (15.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3802.00 (15.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e48.00 (15.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eformer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5422.00 (21.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5319.00 (21.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e103.00 (32.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emild\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8929.00 (35.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8814.00 (35.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e115.00 (35.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emoderate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3257.00 (13.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3232.00 (13.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25.00 ( 7.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eheavy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3422.00 (13.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3393.00 (13.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e29.00 ( 9.06)\u003c/p\u003e \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\u003ePhysical activity, min/week\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e583.959 (1202.836)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e587.545 (1206.582)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e321.061 (846.774)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI/kg.m2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29.398 (6.678)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29.382 (6.666)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30.566 (7.422)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.0027\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eno\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12241.00 (43.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12120.00 (43.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e121.00 (31.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eyes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15995.00 (56.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15736.00 (56.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e259.00 (68.16)\u003c/p\u003e \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\u003eDiabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eno\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21001.00 (74.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20749.00 (74.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e252.00 (66.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.0003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eyes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7218.00 (25.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7090.00 (25.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e128.00 (33.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \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\u003e\u0026emsp;Hazard ratios of CVD and all-cause mortality by Parkinson's disease among adults in NHANES 2003\u0026ndash;2018\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=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eDeaths, no./total no.\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWithout parkinson\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWith parkinson\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHR (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP_value\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eAll-cause mortality\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCrude model\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5133/27862\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e135/380\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.44(1.84, 3.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" 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\u003eMode 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5133/27862\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e135/380\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.84(1.43, 2.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" 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\u003eModel 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5133/27862\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e135/380\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.85(1.47, 2.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" 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\u003eModel 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5133/27862\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e135/380\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.84(1.44, 2.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eCVD mortality\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCrude model\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1616/27862\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42/380\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.44(1.97,4.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" 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\u003eMode 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1616/27862\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42/380\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.95(1.32,2.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" 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\u003eModel 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1616/27862\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42/380\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.87(1.27.2.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" 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\u003eModel 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1616/27862\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42/380\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.82(1.24,2.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eModel1:Adjusted for age, sex, marital status, race/ethnicity, education level, family income, and NHANES cycle.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eModel2:Further adjusted for smoking status,Physical activity and alcohol drinking status.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eModel3:Further adjusted for BMI, hypertension,diabetes\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSensitivity analyses,Exclude cancer and who died within 2 years of follow-up\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=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eDeaths, no./total no.\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWithout parkinson\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWith parkinson\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHR (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP_value\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eAll-cause mortality\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCrude model\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3273/22705\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e82/273\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.44(1.84, 3.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" 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\u003eMode 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3273/22705\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e82/273\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.84(1.43, 2.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" 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\u003eModel 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3273/22705\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e82/273\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.73(1.36, 2.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" 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\u003eModel 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3273/22705\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e82/273\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.77(1.38, 2.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eCVD mortality\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCrude model\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1069/22705\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30/273\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.71(1.80,4.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" 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\u003eMode 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1069/22705\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30/273\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.91(1.23,2.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1069/22705\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30/273\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.77(1.17.2.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1069/22705\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30/273\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.82(1.20,2.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eModel1:Adjusted for age, sex, marital status, race/ethnicity, education level, family income, and NHANES cycle.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eModel2:Further adjusted for smoking status,Physical activity and alcohol drinking status.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eModel3:Further adjusted for BMI, hypertension,diabetes\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003csup\u003ea\u003c/sup\u003eData are presented as unweighted number for categorical variables(percentage) and continuous variables(mean (standard error)).\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis cohort study\u0026apos;s findings indicate that Parkinson\u0026apos;s disease (PD) elevates the risk of both cardiovascular disease (CVD) mortality and overall mortality. The robustness of these results was confirmed through subgroup and sensitivity analyses.\u003c/p\u003e\n\u003cp\u003eOur findings on overall mortality rate are consistent with previous research findings.A historical cohort study spanning 11 years revealed a mortality rate of 1.64 (95% CI: 1.21-2.23) \u0026nbsp;among patients with Parkinson\u0026apos;s disease compared to the control group[16]. Similarly, the Sydney and\u0026nbsp;Netherlands\u0026nbsp;multicenter study reported\u0026nbsp;a higher mortality rate in individuals with Parkinson\u0026apos;s Disease (PD) compared to population data[17][18]. A meta-analysis concluded that cognitive impairment/dementia, ageing, late age of onset, male and gait disturbance are risk factors for mortality in PD patients[19].\u003c/p\u003e\n\u003cp\u003eThe literature on cardiovascular disease mortality in people with PD is still limited and controversial. A previous study showed that\u0026nbsp;the risk of ischemic heart disease\u0026nbsp;and\u0026nbsp;in Parkinson\u0026apos;s disease patients remains unchanged compared to the general population (HR 1.1, 95% CI 0.6-2.0)[20].\u0026nbsp;Even\u0026nbsp;some\u0026nbsp;studies\u0026nbsp;suggested\u0026nbsp;that\u0026nbsp;people with Parkinson\u0026apos;s disease have a reduced overall incidence of both ischaemic stroke and heart attack[21][22].\u0026nbsp;However, previous studies have demonstrated that individuals with Parkinson\u0026apos;s disease (PD) may encounter autonomic dysfunction, cardiomyopathy, coronary heart disease, arrhythmia, or sudden cardiac death (SCD), resulting in a higher prevalence of heart failure among PD patients[23][24].\u0026nbsp;In a recent study by Park et al[11]. in South Korea, a nationwide cohort analysis revealed that individuals with Parkinson\u0026apos;s disease may face a greater probability of experiencing cardiovascular events and death compared to those without the condition，it was found that individuals with Parkinson\u0026apos;s disease (PD) had a higher risk of myocardial infarction (HR 1.43 ,95% CI:1.28-1.59), ischemic stroke (HR 1.42,95% CI:1.31-1.54]), congestive heart failure (HR 1.65 ,95% CI:1.52-1.78).\u0026nbsp;Our research findings also indicate that the cardiovascular mortality rate among Parkinson\u0026apos;s patients is higher compared to non-Parkinson\u0026apos;s patients.By utilizing a substantial sample size of American participants, our study contributes to enhancing the overall applicability of these results.\u003c/p\u003e\n\u003cp\u003eAutonomic dysfunction is frequently observed in Parkinson\u0026apos;s disease (PD) and can manifest in the autonomic nervous system, including the heart[25]. In a study conducted on the heart tissue of Parkinson\u0026apos;s disease patients in Japan, it was discovered that 9 out of 11 patients had Lewy bodies present in both tyrosine hydroxylase positive and negative neural processes, this suggests that the postganglionic sympathetic nervous system and intrinsic neurons in the heart play a role in the development of Parkinson\u0026apos;s disease[26].\u0026nbsp;A prospective study conducted in Sweden revealed that diabetes and elevated fasting blood glucose levels were identified as risk factors for Parkinson\u0026apos;s disease (PD). The study also found that a higher neutrophil to lymphocyte ratio (NLR) in the general population was linked to an increased risk of PD. Interestingly, diabetes, fasting glucose, and NLR are all associated with the risk of coronary events or ischemic stroke[12]. So,it is increasingly recognised that PD patients can develop coronary heart disease and ischemic stroke.Then,most Parkinson\u0026apos;s disease patients receive levodopa treatment, which has been shown to increase homocysteine levels in the blood,elevated homocysteine levels have been associated with a higher incidence of cerebrovascular and cardiovascular diseases[19]. Some study also suggest that the relationship between Parkinson\u0026apos;s disease and cardiovascular disease is complex, with overlapping biological mechanisms, including inflammation, insulin resistance, lipid metabolism, and oxidative stress[27]. These scientific discoveries corroborate our study\u0026apos;s perspective, suggesting that Parkinson\u0026apos;s disease (PD) increases the likelihood of mortality associated with cardiovascular disease (CVD).\u003c/p\u003e\n\u003cp\u003eIn our stratified analysis, we identified several factors that influence the association between PD and cardiovascular disease mortality, such as older age, Non-Hispanic White,male, lower BMI, never smoking, and past or current alcohol consumption.Similar to a South Korea study found a negative dose-response relationship between BMI at diagnosis and mortality in patients with Parkinson\u0026apos;s disease (PD), a 10% change in BMI was significantly linked to mortality outcomes[28]. One possible explanation for this negative correlation is that higher BMI affects insulin levels, which may play a beneficial role in dopaminergic neurodegeneration[29]. we identified a significant interaction regarding cardiovascular disease mortality among individuals with Parkinson\u0026apos;s disease, distinguishing between the male and female subgroups.A retrospective study has analyzed the trend of Parkinson\u0026apos;s disease (PD) mortality revealed that males had a mortality rate for PD that was twice as high as females[30]. The gender disparity in Parkinson\u0026apos;s disease development could be attributed to the potential neuroprotective effect of female gonadotropins, especially circulating estradiol, on the dopaminergic system. Research indicates that men typically acquire Parkinson\u0026apos;s disease at a younger age than women, leading to a higher mortality rate in men at an earlier stage, which may counterbalance other risk factors[31]. In the United States, there exists racial and ethnic disparities in access to neurological care, with black and Hispanic patients being less likely than white patients to consult outpatient neurologists. This discrepancy suggests that white patients have a greater likelihood of being diagnosed with Parkinson\u0026apos;s disease[32], possibly attributed to their overall higher socioeconomic status in terms of education and income compared to minority populations. Consequently, this disparity may contribute to the higher cardiovascular disease mortality rates in white individuals with PD in comparison to other racial and ethnic groups.Numerous clinical studies have demonstrated a negative correlation between smoking and the occurrence of Parkinson\u0026apos;s disease in both genders[33][34]. Smoking might have a protective effect against Parkinson\u0026apos;s disease; however, the cause of the higher vulnerability to cardiovascular disease mortality in Parkinson\u0026apos;s disease patients who have never smoked remains unclear.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStudy strengths and limitations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study is the first to examine cardiovascular disease mortality in Parkinson\u0026apos;s disease patients using data from the NHANES. The sample size was both large and representative, allowing for a more comprehensive analysis. However there were some limitations to this study. Initially, it is critical to note that the determination of Parkinson\u0026apos;s disease (PD) within our research was reliant on participants\u0026apos; self-reported medication usage, without corroboration through a formal medical diagnosis. This approach acknowledges the possibility that a subset of participants may be either unaware of their PD status or may exhibit milder symptoms not necessitating pharmacological intervention, potentially leading to an underrepresented sample.Moreover, we are mindful that patients with tremor-associated neurological conditions other than PD might be prescribed antiparkinsonian medications, yet lack a definitive PD diagnosis. Such instances could precipitate misclassification within our study, thereby introducing a bias into our research outcomes.To address these limitations, future investigations should endeavor to adopt more rigorous diagnostic methodologies. This might entail comprehensive clinical evaluations by specialists in movement disorders or the employment of standardized diagnostic instruments. By integrating these refined diagnostic practices, the accuracy of PD case identification can be enhanced, thereby mitigating the risk of misclassification.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis large cohort study suggests that individuals with Parkinson\u0026apos;s disease (PD) have a higher risk of cardiovascular disease (CVD) mortality compared to those without PD. The association appears to be stronger in older age, Non-Hispanic White individuals, males, those with lower BMI, non-smokers, and those who currently or previously consumed alcohol. Future research should delve deeper into the biological mechanisms underlying this relationship to develop effective strategies for reducing CVD mortality in individuals with PD.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors thank the NHANES staff, investigators, and participants. We thank Dr Liu Jie (People\u0026apos;s Liberation Army of China General Hospital, Beijing, China) for assistance with this revision.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLi\u0026nbsp;Ke wrote the first draft of the manuscript. All authors performed the conceptualization, methods, data collection and analysis, commented on previous versions of the manuscript, contributed to the study conception and design, and read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work has not received any specific grant from any funding in the public, commercial or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that the research was carried out without any without any commercial or financial relationship that could be construed as a potential that could be construed as a potential conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe NHANES obtained approval from the National Center for Health Statistics Research Ethics Review Board and was performed in accordance with the ethical standards as laid down in the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are openly available in [NHANES] at [https://www.cdc.gov/nchs/nhanes/index.htm].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eDexter DT, Jenner P. 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Int J Epidemiol. 2019;48(3):912\u0026ndash;25. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/ije/dyy230\u003c/span\u003e\u003cspan address=\"10.1093/ije/dyy230\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"lipids-in-health-and-disease","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"lhad","sideBox":"Learn more about [Lipids in Health and Disease](http://lipidworld.biomedcentral.com/)","snPcode":"12944","submissionUrl":"https://submission.nature.com/new-submission/12944/3","title":"Lipids in Health and Disease","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"NHANES, cardiovascular disease mortality, Parkinson's disease","lastPublishedDoi":"10.21203/rs.3.rs-4395199/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4395199/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground and Aim\u003c/h2\u003e \u003cp\u003e: Previous studies have produced conflicting results on the association between Parkinson's disease (PD) and cardiovascular disease (CVD) mortality in different populations. Therefore, it is critical to examine the association between PD and CVD mortality specifically in the US population.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eIn this cohort investigation, we enrolled 28,242 participants from the NHANES spanning from 2003 to 2018. The 380 cases of PD in the cohort were identified by documenting \"ANTIPARKINSON AGENTS\" in their reported prescription medications. Mortality outcomes were ascertained by cross-referencing the cohort database with the National Death Index, which was last updated on 31 December 2019. Cardiovascular disease (CVD) mortality was categorised according to the 10th revision of the International Classification of Diseases using a spectrum of diagnostic codes. Weighted multivariable Cox regression analysis was used to examine the association between PD and the risk of CVD mortality.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eAmong 28242 adults included in the study (mean age, 60.156 (12.55) years, 13766 men (48.74%) ), median follow-up period was 89 months. Individuals with PD had an adjusted HR of 1.82 (95% CI, 1.24\u0026ndash;2.69; p\u0026thinsp;=\u0026thinsp;0.002) for CVD mortality and 1.84 (95% CI, 1.44\u0026ndash;2.33; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) for all-cause mortality compared to those without PD. The association between PD and CVD mortality was robust in sensitivity analyses, after excluding participants who died within 2 years of follow-up and those with a history of cancer at baseline (HR,1.82 (95% CI, 1.20\u0026ndash;2.75; p\u0026thinsp;=\u0026thinsp;0.005).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eParkinson's disease was associated with a higher long-term CVD mortality rate in the US population.\u003c/p\u003e","manuscriptTitle":"Association between Parkinson's disease and cardiovascular disease mortality: A prospective population-based study from NHANES","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-03 14:35:50","doi":"10.21203/rs.3.rs-4395199/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-06-07T05:38:54+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-06-05T08:43:32+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-05-29T10:05:32+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"76888809652012140456136389640119803037","date":"2024-05-23T09:16:47+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"333264757824715917030667327253499156289","date":"2024-05-23T05:59:42+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"37954365813672733337437452461021155713","date":"2024-05-22T02:39:54+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-05-17T09:43:43+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-05-17T08:18:07+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-05-17T07:51:53+00:00","index":"","fulltext":""},{"type":"submitted","content":"Lipids in Health and Disease","date":"2024-05-09T12:37:03+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"lipids-in-health-and-disease","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"lhad","sideBox":"Learn more about [Lipids in Health and Disease](http://lipidworld.biomedcentral.com/)","snPcode":"12944","submissionUrl":"https://submission.nature.com/new-submission/12944/3","title":"Lipids in Health and Disease","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"cbdbad33-5a98-4089-bbec-f0fe23dbfd04","owner":[],"postedDate":"June 3rd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2024-06-27T13:56:59+00:00","versionOfRecord":[],"versionCreatedAt":"2024-06-03 14:35:50","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4395199","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4395199","identity":"rs-4395199","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}